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Jiang, Ge. "Essays in evolutionary game theory." Thesis, University of Essex, 2016. http://repository.essex.ac.uk/16917/.
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This thesis contains three essays in evolutionary game theory. In the first chapter, we study the impact of switching costs on the long run outcome in 2X2 coordination games played in the circular city model of local interactions. We find that for low levels of switching costs, the risk dominant convention is the unique long run equilibrium. For intermediate levels of switching costs the set of long run equilibria contains the risk dominant convention but may also contain conventions that are not risk dominant. For high levels of switching costs also nonmonomorphic states will be included in the set of LRE. We study the impact of location heterogeneity on neighborhood segregation in the one-dimensional Schelling residential model in the second chapter. We model location heterogeneity by introducing an advantageous node, in which a player’s utility is impartial to the composition of her neighborhood. We find that when every player interacts with two neighbors, one advantageous node in the circular city will lead to a result that segregation is no longer the unique LRE. When players interact with more neighbors, more advantageous nodes are necessary to obtain the same result. In the third chapter, we consider a model of social coordination and network formation, where players of two groups play a 2X2 coordination game when connected. Players in one group actively decide on whom they play with and on the action in the game, while players in the other group decide on the action in the game only. We find that if either group’s population size is small in comparison to the linking restriction, all players will choose the risk dominant equilibrium, while when both groups are sufficiently large in population, the players of two groups will coordinate on the payoff dominant action.
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Ghachem, Montasser. "Essays in Evolutionary Game Theory." Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-132433.
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Evolutionary game theory tries to explain the emergence of stable behaviors observed in human and animal societies. Prominent examples of such behaviors are cooperative and conformist behaviors. In the first part of the thesis, we develop a model of indirect reciprocity with institutional screening to study how institutions may promote cooperative behavior. We show that cooperation can emerge if screening institutions are sufficiently reliable at identifying cooperators. The second part presents a large-population learning model in which individuals update their beliefs through time. In the model, only one individual updates his beliefs each period. We show that a population, playing a game with two strategies, eventually learns to play a Nash equilibrium. We focus on coordination games and prove that a unique behavior arises both when players use myopic and perturbed best replies. The third part studies the payoff calculation in an evolutionary setting. By introducing mutual consent as a requirement for game play, we provide a more realistic alternative way to compute payoffs.<br><p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript.</p>
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Tsakas, Elias. "Essays on epistemology and evolutionary game theory." Göteborg : Dept. of Economics, School of Economics and Commercial Law, Göteborg University, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016654920&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
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Wallace, Christopher Conor. "Evolutionary game theory in the social sciences." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322749.
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Beauparlant, Marc A. "Evolutionary Game Theory and the Spread of Influenza." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35635.
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Vaccination has been used to control the spread of infectious diseases for centuries with widespread success. Deterministic models studying the spread of infectious disease often use the assumption of mass vaccination; however, these models do not allow for the inclusion of human behaviour. Since current vaccination campaigns are voluntary in nature, it is important to extend the study of infectious disease models to include the effects of human behaviour. To model the effects of vaccination behaviour on the spread of influenza, we examine a series of models in which individuals vaccinate according to memory or individual decision-making processes based upon self-interest. Allowing individuals to vaccinate proportionally to an exponentially decaying memory function of disease prevalence, we demonstrate the existence of a Hopf bifurcation for short memory spans. Using a game-theoretic influenza model, we determine that lowering the perceived vaccine risk may be insufficient to increase coverage to established target levels. Utilizing evolutionary game theory, we examine models with imitation dynamics both with and without a decaying memory function and show that, under certain conditions, periodic dynamics occur without seasonal forcing. Our results suggest that maintaining diseases at low prevalence with voluntary vaccination campaigns could lead to subsequent epidemics following the free-rider dilemma and that future research in disease control reliant on individual-based decision-making need to include the effects of human behaviour.
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Norman, William. "Evolutionary Game Dynamics and the Moran Model." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-420672.
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Treacy, Brian. "A stochastic differential equation derived from evolutionary game theory." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-377554.
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JAVARONE, MARCO ALBERTO. "Statistical Physics of Evolutionary Game Theory and its Applications." Doctoral thesis, Università degli Studi di Cagliari, 2017. http://hdl.handle.net/11584/249581.
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Evolutionary Game Theory represents a vibrant and interdisciplinary research field, that is attracting the interest of scientists belonging to different communities, spanning from physicists to biologists, and from mathematicians to sociologists. In few words, it represents the attempt to study the evolutionary dynamics of a population by the framework of Game Theory, taking into account the Darwinian theory of natural evolution. As result, Evolutionary Game Theory allows to model a number of scenarios, as social and biological systems, with a high level of abstraction. On one hand, the contribution of the classical Game Theory can be identified at a local level, i.e. in the interactions among the agents. For instance, when agents play games like the Prisoner’s Dilemma, according to the Nash Equilibrium, they should defect. On the other hand, in some conditions, it is possible to observe final equilibria far from the expected one. Notably, here we identify the contribution of the Darwinian theory, since the agents can change their behavior according to adaptive mechanisms. Remarkably, often populations reaching non-expected equilibria show emergent behaviors, resulting from their interaction pattern, or from specific local behaviors. For this reason, evolutionary games must be considered as complex systems. Accordingly, we believe that statistical physics constitutes one of the most suitable approaches for studying and understanding their underlying dynamics. In this scenario, one of the aims of this dissertation is to illustrate some models that let emerge a direct link between Evolutionary Game Theory and statistical physics. In addition, we show that the link between the two fields allows to envision new applications beyond the current horizon of Evolutionary Game Theory, as defining optimization strategies. So, at the beginning, we focus on a statistical physics model devised for understanding ’why’ random motion, in continuous spaces (and within a particular speed range), is able to trigger cooperation in the Prisoner’s Dilemma. Then, we study the role of the temperature in the spatial Public Goods Game, defining a link between this game and the classical Voter Model. Eventually, mapping strategies to spins, we study the spatial Public Goods Game in presence of agents susceptible to local fields, i.e. fields generated by their nearest-neighbors. It is worth to note that, from a social point of view, an agent susceptible to a local field can be considered as a conformist, since it imitates the strategy (or behavior) of majority in its neighborhood. Later, we propose three applications of Evolutionary Game Theory. In particular, the first one is a new method for solving combinatorial optimization problems. The second application is focused on the definition of a game for studying the dynamics of Poker challenges. Finally, the third application aims to represent a phenomenon of social evolution, named group formation. To conclude, we deem that the achieved results shed new light on the relation between Evolutionary Game Theory and Statistical Physics, and allow to get insights useful to devise new applications in different domains.
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Rael, Rosalyn Cherie. "Comparing theory and data on multi-species interactions using evolutionary game theory." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/194398.
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Mathematical models with fixed parameters have a long history of use in describing the dynamics of populations in ecological interactions. However, in many instances, evolutionary changes in species characteristics can have a significant influence on these dynamics. Using evolutionary game theory, we incorporate evolution into population dynamic models and apply the resulting “Darwinian dynamic” models to study the effects that evolutionary changes can have on populations in several ecological scenarios. We start with a single species (Chapter 2), then add a competitor (Chapter 3), and a predator (Chapter 4). In Chapter 2, a rigorous mathematical analysis of the Darwinian logistic model for a single species shows that stable equilibria occur at strategies that maximize population size rather than growth rate. We apply this model to the data obtained from an experimental study on genetically perturbed populations of the flour beetle Tribolium castaneum. In Chapter 3, we apply a Darwinian dynamic modification of the Lotka-Volterra model to investigate circumstances under which evolution will change expected competitive outcomes. We compare the results of our Darwinian Lotka-Volterra model to studies in which unusual observations were made in studies of the flour beetles T. castaneum and T. confusum, including a reversal in the “winner” of competitive exclusion, and evolution from exclusion to coexistence. Chapters 2 and 3 provide one of the few examples in which evolutionary game theory has been successfully applied to empirical data. From a foundation provided by the Darwinian logistic equation, we build Darwinian dynamic models with two and three trophic levels to study effects of evolution on some basic ecological interactions in Chapter 4. We show how a consumer can cause a resource (producer) species to evolve to a mean strategy that increases its growth rate rather than its population size. We also briefly study how predation on the consumer species can affect equilibrium strategies of species lower in the food chain. Our results show how evolutionary game theoretic methods can be useful for studying both theoretical and applied problems that arise due to evolutionary processes, even when they occur on a ecological time scale. They provide a foundation for the future study of evolutionary effects in larger complex networks of interacting species.
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SALOMAO, GABRIEL MEYER. "ENVIRONMENTAL POLICY REGULATION FROM THE PERSPECTIVE OF EVOLUTIONARY GAME THEORY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31461@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>Um dos principais desafios do mundo moderno é equilibrar o desenvolvimento econômico com a responsabilidade ambiental, de forma a alcançar um crescimento sustentável que minimize os impactos gerados no meio ambiente. Isto tem feito com que muitos governos e empresas estabeleçam políticas ambientais como instrumentos para a garantia de um futuro com sustentabilidade e que favoreçam o bem estar social. A proposta desta dissertação é utilizar a teoria dos jogos evolucionários para analisar as interações entre agentes reguladores de políticas ambientais de comando e controle e os agentes (firmas) que impulsionam o desenvolvimento econômico, porém que impactam de alguma forma o meio ambiente. Enquanto os primeiros precisam determinar as melhores ações estratégicas para implementar a política e aumentar o bem estar social, os segundos só irão se adequar à regulamentação ambiental estabelecida se esta escolha lhe render um maior retorno (payoff). Os resultados mostram que o custo de fiscalização é determinante para estabelecer a política ambiental mais adequada e, dependendo da magnitude deste custo, existem diferentes formas de iniciar sua implementação a fim de favorecer o melhor resultado possível sob o ponto de vista do bem estar social.<br>The modern world faces the great challenge of balancing economic development and environmental responsibility in order to achieve sustainable growth that minimizes the impacts generated on the environment. This has forced some governments and firms establish environmental policies as instruments to guarantee a future with sustainability and favors social welfare. Using evolutionary games theory, this work aims to analyze the interactions between environmental policies regulators and firms that provide economic development impacting the environment. While the firsts need to choose the best strategic actions to established and inspect environmental standards sets to increase social welfare, the company will only complies if this choice yields a better payoff. The results show how the inspection cost is decisive for establishing the better environmental policy and depending on the magnitude of this cost, there are different ways to introduce it in order to provide a better social welfare result.
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He, Qian. "Spatio-Temporal Patterns, Correlations, and Disorder in Evolutionary Game Theory." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/40296.
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Evolutionary game theory originated from the application of mathematical game theory to biological studies.
Well-known examples in evolutionary game theory are the prisoner's dilemma, predator-prey models, the rock-paper-scissors game, etc.
Recently, such well-known models have attracted increased interest in population dynamics to understand the
emergence of biodiversity and species coexistence. Meanwhile, it has been realized that techniques from statistical
physics can aid us to gain novel insights into this interdisciplinary field. In our research, we mainly employ
individual-based Monte Carlo simulations to study emerging spatio-temporal patterns, spatial correlations,
and the influence of quenched spatial disorder in rock-paper-scissors systems either with or without conserved
total population number. In balanced rock-paper-scissors systems far away from the ``corner'' of configuration space,
it is shown that quenched spatial disorder in the reaction rates has only minor effects on the co-evolutionary dynamics.
However, in model variants with strongly asymmetric rates (i.e., ``corner'' rock-paper-scissors systems),
we find that spatial rate variability can greatly enhance the fitness of both minor species in``corner'' systems,
a phenomenon already observed in two-species Lotka-Volterra predator-prey models. Moreover, we numerically study the
influence of either pure hopping processes or exchange processes on the emergence of spiral patterns in spatial
rock-paper-scissors systems without conservation law (i.e., May-Leonard model). We also observe distinct extinction
features for small spatial May-Leonard systems when the mobility rate crosses the critical threshold which separates
the active coexistence state from an inactive absorbing state.
In addition, through Monte Carlo simulation on a heterogeneous interacting agents model,
we investigate the universal scaling properties in financial markets such as the fat-tail distributions in return and trading volume,
the volatility clustering, and the long-range correlation in volatility. It is demonstrated that the long-tail feature in trading volume distribution
results in the fat-tail distribution of asset return, and furthermore it is shown that the long tail in trading volume
distribution is caused by the heterogeneity in traders' sensitivities to market risk.<br>Ph. D.
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Chakeri, Alireza. "Scalable Unsupervised Learning with Game Theory." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6616.
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Recently dominant sets, a generalization of the notion of the maximal clique to edge-weighted graphs, have proven to be an effective tool for unsupervised learning and have found applications in different domains. Although, they were initially established using optimization and graph theory concepts, recent work has shown fascinating connections with evolutionary game theory, that leads to the clustering game framework. However, considering size of today's data sets, existing methods need to be modified in order to handle massive data. Hence, in this research work, first we address the limitations of the clustering game framework for large data sets theoretically. We propose a new important question for the clustering community ``How can a cluster of a subset of a dataset be a cluster of the entire dataset?''. We show that, this problem is a coNP-hard problem in a clustering game framework. Thus, we modify the definition of a cluster from a stable concept to a non-stable but optimal one (Nash equilibrium). By experiments we show that this relaxation does not change the qualities of the clusters practically.
Following this alteration and the fact that equilibriums are generally compact subsets of vertices, we design an effective strategy to find equilibriums representing well distributed clusters. After finding such equilibriums, a linear game theoretic relation is proposed to assign vertices to the clusters and partition the graph. However, the method inherits a space complexity issue, that is the similarities between every pair of objects are required which proves practically intractable for large data sets. To overcome this limitation, after establishing necessary theoretical tools for a special type of graphs that we call vertex-repeated graphs, we propose the scalable clustering game framework. This approach divides a data set into disjoint tractable size chunks. Then, the exact clusters of the entire data are approximated by the clusters of the chunks. In fact, the exact equilibriums of the entire graph is approximated by the equilibriums of the subsets of the graph. We show theorems that enable significantly improved time complexity for the model. The applications include, but are not limited to, the maximum weight clique problem, large data clustering and image segmentation. Experiments have been done on random graphs and the DIMACS benchmark for the maximum weight clique problem and on magnetic resonance images (MRI) of the human brain consisting of about 4 million examples for large data clustering. Also, on the Berkeley Segmentation Dataset, the proposed method achieves results comparable to the state of the art, providing a parallel framework for image segmentation and without any training phase. The results show the effectiveness and efficiency of our approach.
In another part of this research work, we generalize the clustering game method to cluster uncertain data where the similarities between the data points are not exactly known, that leads to the uncertain clustering game framework. Here, contrary to the ensemble clustering approaches, where the results of different similarity matrices are combined, we focus on the average utilities of an uncertain game. We show that the game theoretical solutions provide stable clusters even in the presence of severe uncertainties. In addition, based on this framework, we propose a novel concept in uncertain data clustering so that every subset of objects can have a ''cluster degree''. Extensive experiments on real world data sets, as well as on the Berkeley image segmentation dataset, confirm the performance of the proposed method.
And finally, instead of dividing a graph into chunks to make the clustering scalable, we study the effect of the spectral sparsification method based on sampling by effective resistance on the clustering outputs. Through experimental and theoretical observations, we show that the clustering results obtained from sparsified graphs are very similar to the results of the original non-sparsified graphs. The rand index is always at about 0.9 to 0.99 in our experiments even when lots of sparsification is done.
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Hugie, Don Michael. "Applications of evolutionary game theory to the study of predator-prey interactions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ52711.pdf.
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Chen, J.-H. "An automated negotiation mechanism based on co-evolutionary processes and game theory." Thesis, Coventry University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427568.
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Izquierdo, Luis R. "Advancing learning and evolutionary game theory with an application to social dilemmas." Thesis, Manchester Metropolitan University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444030.
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Geoffroy, Félix. "Explaining fine-grained properties of human cooperation : Insights from evolutionary game theory." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTG071/document.
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L'existence, dans de nombreuses espèces, de comportements coopératifs entre individus non-apparentés constitue un paradoxe apparent pour la théorie de l'évolution. L'explication la plus acceptée est que les comportements coopératifs peuvent être « incités » par un mécanisme qui récompense les coopérateurs et punit les tricheurs. On parle alors de « coopération conditionnelle ». La majorité des travaux en théorie des jeux évolutionnaires cherchent seulement à expliquer comment des comportements coopératifs en général peuvent exister à un équilibre évolutionnaire. Dans cette thèse, nous cherchons au contraire à montrer que la théorie des jeux évolutionnaires peut aussi permettre de comprendre certaines des propriétés fines des comportements coopératifs qu'on observe dans le vivant, en particulier dans le cas de l'espèce humaine. Tout d'abord, nous posons la question de l'origine de la coopération conditionnelle. Comment la coopération conditionnelle peut-elle évoluer à partir d'une situation initiale dans laquelle personne ne coopère ? A l'aide de méthodes empruntées à l'apprentissage automatique, nous montrons que la coopération conditionnelle peut évoluer en tant que sous-produit d'une adaptation à des interactions dans lesquelles les intérêts des participants sont alignés. Nous montrons également que ce processus évolutif ne peut aboutir qu'à deux résultats opposés. Soit toutes les opportunités de coopération sont « trouvées » par l'évolution, ce qui correspond à la prévalence des comportements coopératifs chez l'Homme, soit un nombre très réduit d'opportunités de coopération sont « trouvées », ce qui correspond aux comportements coopératifs non humains. Nous proposons également une variante de ce modèle qui permet d'expliquer pourquoi de nombreux mutualismes sont des formes exagérées de cas d'interactions basées sur des intérêts communs. Dans un second temps, nous nous concentrons sur un mécanisme particulier de coopération conditionnelle : le choix du partenaire. Nous utilisons des simulations individu-centrées, et nous montrons que si l'on peut choisir librement ses partenaires dans la coopération, alors le seul niveau d'effort investi dans la coopération qui est évolutivement stable est celui qui maximise l'efficacité sociale de la coopération. Puis, nous développons des modèles analytiques, importés de la théorie économique des appariements. Nous montrons que la seule distribution des bénéfices générés par la coopération qui est évolutivement stable ne dépend pas des rapports de force et est proportionnelle à la contribution de chacun des participants. Ainsi, la théorie du choix du partenaire explique deux propriétés fines des comportements coopératifs chez l'Homme : nos préférences pour les formes de coopération les plus socialement efficaces et notre sens de l'équité. Enfin, nous montrons que la théorie des signaux coûteux, appliquée à la coopération, peut expliquer plusieurs propriétés de la réputation morale, puis nous concluons en discutant de futures directions de recherche<br>The existence of cooperation among non-kin in many species constitutes an apparent paradox for evolutionary biologists. The most commonly accepted explanation is that cooperation can be enforced by mechanisms that reward cooperators or punish cheaters. Most of the theoretical works in evolutionary game theory, however, aim only at explaining how some cooperation can exist at an evolutionary equilibrium, thanks to these enforcement mechanisms. Here, we aim at showing, instead, that evolutionary game theory can also explain the fine-grained properties of the cooperation that takes place in the living world, especially in the case of the human species. First, we address the question of the origin of enforced cooperation: How can enforced cooperation evolve from an initially non-cooperative state? Using tools from the field of machine learning, we show that enforced cooperation can evolve as a by-product of adaptation to interactions with shared interests. We also show that this process has only two possible evolutionary outcomes. Either all cooperative opportunities are enforced, which corresponds to the human cooperative syndrome, or only a very few number are, which corresponds to non-human cooperation. We also propose a variation of this model to explain why many mutualisms are exaggerated forms of cooperation with shared interests. In a second approach, we focus on one specific enforcement mechanism called partner choice. Using agent-based simulations, we show that, when individuals can freely choose their cooperative partners, the only level of effort invested into cooperation that is evolutionarily stable is the one that maximizes the social efficiency of cooperation. We then build analytical models of partner choice imported from economic matching theory. We show that the only evolutionarily stable distribution of the benefits of cooperation is both independent of bargaining power and proportional to each participant's relative contribution. Thus, partner choice explains two fine-grained properties of human cooperation, namely our preferences for the most socially efficient forms of cooperation and our concerns for fair distributions. Finally, we show that costly signalling models of cooperation can explain several properties of moral reputation, and we conclude by discussing directions for future research
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Fryer, Timothy James Osborne. "ESS models of sperm competition." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266803.
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vicario, eugenio. "Essays on Segregation, Minorities, and Imitation." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1107924.
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The thesis is composed by three chapters. The common theme of the three essays is the identification of long run equilibria of games played on regular networks where interactions are at local level. In the first and second chapter I contribute to distinct literatures applying technics and results from the literature on evolutionary game theory with local interactions. The study of economic segregation within towns, and the tendency of ethnic minorities to live in ethnic enclaves are at the center of the first and the second chapter respectively. In the third chapter a refinement of previous results in the theoretical literature on evolutionary game theory with local interactions is given. In the thesis I develop models with different specifications of revision opportunities, error models, and behavior of agents, which require different techniques for the selection of the long run equilibria. The spatial structure is common to the three chapters, in fact agents are deployed on lattices with periodic boundary conditions. In the first chapter the spatial structure is given by a two dimensional lattice, i.e a torus, in the third chapter a one dimensional lattice, i.e. a ring, is used, while in the second chapter I use both the specifications. The network is always fixed and exogenously given, and the concept of continuous neighborhood is used. Neighborhoods are said to be continuous when are based on the individual perception of agents. Each agent is in the middle of his own neighborhood, and then the neighborhoods of different agents may partially overlap but never coincide. This in contrast with the concept of bounded neighborhoods where agents belonging to the same neighborhood share all the neighbors. In this last case neighborhoods form a partition of the set of agents. Following the literature on continuous neighborhood the two main specifications are considered, in fact are used both the Moore and the Von Neumann neighborhoods in the two dimensional lattice. In the one dimensional lattice models different dimensions of the neighborhood are considered. In the first chapter agents move within the network exchanging position each other. In every period two agents are selected and switch position if both will be better off in the new neighborhood. Differently in the second and third chapter agents do not move within the network while instead they revise their strategy based on the strategies of neighbors. The timing of revision opportunities is another fundamental ingredient of the three models. In the first and the second chapter asynchronous revision opportunities are modeled, in fact in the first chapter only one couple per time has the possibility to switch position, while in the second chapter only one agent per turn revises the strategy. In the third chapter the revision opportunities are simultaneous, and all the agents revise their strategy in each period.
In the three chapter, as usual in evolutionary game theory, agents have bounded rationality. In fact agents have a myopic behavior, they are unable to make any prevision about the future states, and then revise their strategy only considering the actual state. In the third chapter a further level of irrationality is given by the fact that agents, instead
of best replying to the actual situation, as in the first and second chapter, imitate the action of the best performing neighbor. A stochastically stable state is a state that is observed with a positive probability in the long run in presence of a small perturbation. The perturbation is at the individual level, in fact each agent, in every moment, has a small but positive chance to make a decision differently from that prescribed by his behavioral rule. The perturbation in biology is used to model mutations, while in economics the noise is represented by mistakes and experimentations. Through the introduction of a small amount of noise is possible to define a perturbed transition matrix for which is possible to move from any state of the world to any other in a finite number of steps. In the first chapter the behavior of agents is described by a logit choice function, for which costly mistakes are less likely. Each agent has a positive probability to accept or not an exchange, depending on the variation of utility obtained with the exchange. The game can be described by a potential function defined on the set of strategies of agents, for which every change in the utility of agents is reflected in a variation of the potential function. Assuming the logit choice rule and in the presence of asynchronous revision opportunities, in a potential game the stochastically stable states coincide with states having maximum potential. In this setting is sufficient to study the potential function to select the set of long run equilibria.
In the second and third chapter a uniform error model is implemented. Each error can occur with the same probability, independently from how costly it is. In the second chapter three versions of the model are developed. In the first version there is not a spatial structure and interactions are at the global level. The identification of stochastically stable states is obtained using the technique developed by Young (1993), based on results by Freidlin and Wentzell (1984). At the basis of this technique there is the construction of rooted trees, made by the least resistance paths from each absorbing set to each other, where an absorbing set is a minimal set from which the unperturbed process can not escape. Between the paths connecting an absorbing set to another one the least resistance path is the one that is more likely to be observed. The summation of the resistance of all the least resistance paths ending in an absorbing set, E, and starting from all the other absorbing sets is the stochastic potential of the absorbing set E. The absorbing sets with minimal stochastic potential are the stochastically stable sets. The application is relatively simple having only two absorbing sets connected by only one path. In the second version of the model agents are deployed on a two dimensional lattice and interact only with a set of neighbors and the result is obtained via simulations. There are many advantages in the use of simulations, but also some limitations. In fact when the probability of a transition out from an absorbing set is very low it is unlikely to observe it during a simulation, and may be difficult to asses which transition is more likely. When the error rate is higher transitions are more likely but the perturbation may affect too much the dynamics. In the third version agents are deployed on one dimensional lattice, as in the third chapter. The radius coradius technique proposed by Ellison (2000) is used to identify the stochastically stable sets. The basic idea is to compute the radius and the coradius of all the absorbing sets and compare them. The radius represents how is difficult to leave the basin of attraction of an absorbing set, while the difficulty to enter into the basin of attraction of an absorbing set is measured by the coradius. The stochastically stable set of the model is contained in the subset of absorbing sets having radius greater then coradius.
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TALARICO, AGOSTINO. "Evolutionary games on networks for modeling spontaneous brain functioning." Doctoral thesis, Università di Siena, 2017. http://hdl.handle.net/11365/1013401.
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Our brain is a complex system of interconnected regions spontaneously organized into
distinct networks. The integration of information between and within these networks
is a continuous process that can be observed even when the brain is in a quiescent
state at rest. In fact, the same brain regions contributing to our ability to think, speak
and remember, show coordinated activity also while we are not engaged in specific
tasks, suggesting that it is a preparatory state for any subsequent activity. Moreover,
such spontaneous dynamics show predictive value over individual cognitive profile and
constitutes a potential marker in pathological condition, thus making its understanding
a crucial quest for modern neuroscience. However, how and why such complex,
spontaneous activity emerges is still unknown.
In this thesis work, it is presented a theoretical and mathematical model where the
interaction between brain regions can be modeled as an evolutionary game on network
(EGN); here, each region behaves as a player which maximizes its fitness by monitoring
other players behaviour. The proposed model, labeled as EGN-B, is based on
nonlinear emulative and non-emulative behaviors, where the balancing between these
two attitudes is responsible for the net behavior of nodes composing resting-state networks
identified using functional magnetic resonance imaging (fMRI), determining
their moment-to-moment level of activation and inhibition as expressed by spontaneous
positive and negative shifts in BOLD fMRI signal. By spontaneously generating
low-frequency oscillatory behaviors, EGN-B model is able to mimic network dynamics,
approximate fMRI time series on the basis of an initial subset of available input, as
well as simulate the impact of network lesions, providing initial evidence of compensation
mechanisms across networks. Results suggest EGN as a new potential framework
for the understanding of human brain network dynamics.
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Nokleby, Matthew S. "Satisficing Theory and Non-Cooperative Games." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2318.pdf.
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Bhogal, Manpal Singh. "Physical attractiveness, altruism and fairness in a game-theoretic framework." Thesis, University of Wolverhampton, 2017. http://hdl.handle.net/2436/620508.
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Altruism and cooperation have been troubling concepts for theorists. Where altruism towards kin is well-researched, altruism towards non-kin is an evolutionary puzzle. There have been advances in evolutionary psychology where theorists have explored the evolution of altruism through the lens of sexual selection theory, hypothesising that altruism leads to increased chances of being chosen as a mate, particularly as females value altruistic tendencies in a romantic partner. As a result, it was hypothesised males would be more cooperative and altruistic towards those they were attracted to. In study 1, it was found that females placed more importance on altruism and cooperativeness in a mate, far more than males. In addition, males placed more importance on physical attractiveness in a mate, far more than females. In study 2, it was found that people were altruistic and cooperative towards attractive members of the opposite sex when viewing images in response to moral scenarios. When I aimed to replicate this finding, using a game-theoretic framework in studies 3, 4 and 5, I found that people were fair, and altruistic when allocating stakes, and attractiveness did not predict altruism. This consistent fair behaviour led me to further investigate the role of fairness in mate attraction. In studies 6 and 7, it was found that third-parties found fairness to be more attractive than altruism, particularly female participants. In study 8, I further delved into the role of fairness in mate choice, where I found that fairness could be attractive because it increases relationship maintenance in the short-term, but it is altruism that increases relationship longevity in long-term relationships. Furthermore, it was found that people perceive short-term, fair couples to have less intention to cheat than long-term altruistic couples. This thesis opens a new and exciting door in the field of evolutionary psychology, providing evidence that fairness could play a role in mate choice.
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Crosby, Garth Valentine. "Trust Based Security Mechanisms for Wireless Sensor Networks." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/61.
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Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.
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Gu, Shangdong. "From Rock Scissor Paper to study and modeling of Chinese Five Elements : Evolutionary Game Theory." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23788.
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In this thesis, we have developed a model to study the behavior of an extended version of evolutionary game "Rock-Scissor-Paper", that is "Five Elements". The origin of five elements are from "Chinese five elements" in which five different types of elements compete with each other in a similar way as in a SIR model. Elements are affecting each other in two different ways, either to compete with each other or to help some particular elements in resisting their superior elements. The competition and cooperation is linked in circle which initiates a steady state. The analytical expressions (mean field) and simulation results have been presented. We have made some basic simulations of the original "Rock-Scissor-Paper" in order to build a better understanding of this kind of evolutionary game, and to extend from three elements to five elements. One of the real examples of five elements we have studied is a game called "Rock-Paper-Scissor-Lizard-Spock", which is a direct extension from the "Rock-Scissor-paper". Cooperation in the game is expressed in form of either direct cooperation/help from different elements as in "Chinese Five Elements" or indirect help caused by direct competition. Based on the simulations, some characteristic behaviors of five elements have been found. Reaction rates and different competition probabilities have proven to be the critical part in the game.
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Gaddoni, Giacomo. "Modeling of Evolutionary Cancer Dynamics and Optimal Treatment via Dynamic Programming." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
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Cancer is one of the biggest challenges in healthcare. Fast diagnosis and personalized pharmacological therapies are essential for lowering the mortality rate. In this thesis, we propose a general-purpose model for cancer and an optimal control strategy to minimize its volume. Firstly, we analyze the literature about cancer in the System and Control community and produce a taxonomy of cancer typologies. We identify four main behaviors arising in these models: growth, mutation, migration, and drug response. After this preliminary analysis, we propose a cancer treatment model based on Ordinary Differential Equations (ODEs) and Evolutionary Game Theory, that captures these dynamics more generally. ODEs provide a framework for lumped-parameters representations, and Evolutionary Game Theory provides tools to describe competitive behaviors typical of these cell populations. Starting from this taxonomy, we chose a model representable with a 2-node graph that expressed all the dynamics of cancer processes. We studied the model, discretized it, and applied an optimal control method based on Differential Dynamic Programming (DDP). Bounded and unbounded DDP were ineffective. It was necessary to introduce regularized DDP via adaptive shift. With this algorithm, the results are promising: the system is successfully stabilized in the origin. It is also possible to control the system, driving it between two equilibria, tracking a demanded trajectory. Most of the testing was done in MATLAB. Then, the project was ported to Python. This was done to facilitate future expansion of the model and control strategies through scientific analysis toolboxes and frameworks.
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Magner, Mark. "The Evolutionary Paradox: Using Nash Equilibria to Understand Microbial Social Interactions." Miami University Honors Theses / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=muhonors1115409924.
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Kasthurirathna, Dharshana Mahesh. "The influence of topology and information diffusion on networked game dynamics." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14570.
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This thesis studies the influence of topology and information diffusion on the strategic interactions of agents in a population. It shows that there exists a reciprocal relationship between the topology, information diffusion and the strategic interactions of a population of players. In order to evaluate the influence of topology and information flow on networked game dynamics, strategic games are simulated on populations of players where the players are distributed in a non-homogeneous spatial arrangement. The initial component of this research consists of a study of evolution of the coordination of strategic players, where the topology or the structure of the population is shown to be critical in defining the coordination among the players. Next, the effect of network topology on the evolutionary stability of strategies is studied in detail. Based on the results obtained, it is shown that network topology plays a key role in determining the evolutionary stability of a particular strategy in a population of players. Then, the effect of network topology on the optimum placement of strategies is studied. Using genetic optimisation, it is shown that the placement of strategies in a spatially distributed population of players is crucial in maximising the collective payoff of the population. Exploring further the effect of network topology and information diffusion on networked games, the non-optimal or bounded rationality of players is modelled using topological and directed information flow of the network. Based on the topologically distributed bounded rationality model, it is shown that the scale-free and small-world networks emerge in randomly connected populations of sub-optimal players. Thus, the topological and information theoretic interpretations of bounded rationality suggest the topology, information diffusion and the strategic interactions of socio-economical structures are cyclically interdependent.
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Slipetz, Lindley. "On Distinguishing the Meaningless from the Meaningful: An Evolutionary Game Theoretic Approach to Ruth Millikan\'s Teleosemantics." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/20377.
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What distinguishes a meaningless utterance from a meaningful term? While one might say that, within the context of Ruth Millikan\'s teleosemantics, it is a term\'s having a proper function that distinguishes it from a meaningless utterance, I propose that the distinction can be made with reference to the history of the term. Using evolutionary game theory, I offer a way to clarify the distinction between the meaningless and the meaningful. I reject the possibility of correlating meaning with an evolutionarily stable strategy as this does not seem to be consistent with how communication works or with Millikan\'s theory. Instead, when a term has meaning, the function category of that term corresponds to an evolutionarily stable state composed of both speaker and hearer strategies.<br>Master of Arts
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Li, Xiang-Yi [Verfasser]. "Applying evolutionary game theory in modeling life history evolution and bacterial population dynamics / Xiang-Yi Li." Kiel : Universitätsbibliothek Kiel, 2016. http://d-nb.info/108193526X/34.
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Kamhoua, Charles A. K. "Modeling Security and Cooperation in Wireless Networks Using Game Theory." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/436.
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This research involves the design, development, and theoretical demonstration of models resulting in integrated misbehavior resolution protocols for ad hoc networked devices. Game theory was used to analyze strategic interaction among independent devices with conflicting interests. Packet forwarding at the routing layer of autonomous ad hoc networks was investigated. Unlike existing reputation based or payment schemes, this model is based on repeated interactions. To enforce cooperation, a community enforcement mechanism was used, whereby selfish nodes that drop packets were punished not only by the victim, but also by all nodes in the network. Then, a stochastic packet forwarding game strategy was introduced. Our solution relaxed the uniform traffic demand that was pervasive in other works. To address the concerns of imperfect private monitoring in resource aware ad hoc networks, a belief-free equilibrium scheme was developed that reduces the impact of noise in cooperation. This scheme also eliminated the need to infer the private history of other nodes. Moreover, it simplified the computation of an optimal strategy. The belief-free approach reduced the node overhead and was easily tractable. Hence it made the system operation feasible. Motivated by the versatile nature of evolutionary game theory, the assumption of a rational node is relaxed, leading to the development of a framework for mitigating routing selfishness and misbehavior in Multi hop networks. This is accomplished by setting nodes to play a fixed strategy rather than independently choosing a rational strategy. A range of simulations was carried out that showed improved cooperation between selfish nodes when compared to older results. Cooperation among ad hoc nodes can also protect a network from malicious attacks. In the absence of a central trusted entity, many security mechanisms and privacy protections require cooperation among ad hoc nodes to protect a network from malicious attacks. Therefore, using game theory and evolutionary game theory, a mathematical framework has been developed that explores trust mechanisms to achieve security in the network. This framework is one of the first steps towards the synthesis of an integrated solution that demonstrates that security solely depends on the initial trust level that nodes have for each other.
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Wang, Xiaohui. "Singularity Theory of Strategy Functions Under Dimorphism Equivalence." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1426460461.
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Chernomaz, Kirill. "Behavior and learning in asymmetric independent private values auctions." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1179508964.
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Matros, Alexander. "Stochastic stability and equilibrium selection in games." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 2001. http://www.hhs.se/efi/summary/571.htm.
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Berger, Ulrich. "Learning to trust, learning to be trustworthy." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/4806/1/wp212.pdf.
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Interpersonal trust is a one-sided social dilemma. Building on the binary trust game, we ask how trust and trustworthiness can evolve in a population where partners are matched randomly and agents sometimes act as trustors and sometimes as trustees. Trustors have the option to costly check a trustee's last action and to condition their behavior on the signal they receive. We show that the resulting population game admits two components of Nash equilibria. Nevertheless, the long-run outcome of an evolutionary social learning process modeled by the best response dynamics is unique. Even if unconditional distrust initially abounds, the trustors' checking option leads trustees to build a reputation for trustworthiness by honoring trust. This invites free-riders among the trustors who save the costs of checking and trust blindly, until it does no longer pay for trustees to behave in a trustworthy manner. This results in cyclical convergence to a mixed equilibrium with behavioral heterogeneity where suspicious checking and blind trusting coexist while unconditional distrust vanishes. (author's abstract)<br>Series: Department of Economics Working Paper Series
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Hedlund, Jonas. "Essays in microeconomic theory." Doctoral thesis, Universidad de Alicante, 2011. http://hdl.handle.net/10045/20509.
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Di, Stefano Alessandro. "Evolutionary Dynamics of Social Behaviours on Multilayer Networks." Doctoral thesis, Università di Catania, 2015. http://hdl.handle.net/10761/3848.
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Nature shows as human beings live and grow inside social structures. This assumption allows explaining and exploring how it may shape most of our behaviours and choices, and why we are not just blindly driven by instincts: our decisions are based on more complex cognitive reasons, based on our connectedness on di erent spaces. Thus, human cooperation emerges from this complex nature of social network. One of the main aims of my Ph.D.
dissertation is to explore how and why it happens, hence the work is mainly focused on studying the evolutionary dynamics of cooperation and social behaviours on a multilayer social network. Following a Bio-inspired approach, the social network analysis methodologies, and exploiting the mathematical framework of Evolutionary Game Theory (EGT), the target is to unveil the hidden dynamics, observe non-trivial patterns, nding out the hidden
emergent behaviours in a population. The study of cooperation and its evolutionary
dynamics on a social network, has raised up the need of a model able to explain the actual complexity of real-world networks, where individuals are connected through multiple types of relationships. For this reason, the mathematical framework of multilayer networks has been exploited, indeed it allows us to encompass these several interactions and relationships, exploring and unveiling how the di erent ties in the various layers can impact
on the emergence of social behaviours in a population. Therefore, the presence of the same nodes in multiple layers of a system, known as multiplexity, is the key to understand emergent phenomena, adding an extra dimension of analysis which explains what is the role not only of the intralayer interactions, as in a single-layer framework, but also of interlayer
interactions for the emergence of these phenomena. Furthermore, it is explored and quanti ed the role of some shaping factors, such as homophily, in this evolutionary process. Taking into account all these aspects, a novel analytical model is proposed, together with a simulative investigation of the evolution of human cooperation using mutliplex evolutionary game theory, shedding light on the key role played by homophily and multiplexity in the
evolution of cooperation. (continue in Ph. D. dissertation)
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Ghoneim, Ayman Ahmed Sabry Abdel Rahman Information Technology & Electrical Engineering Australian Defence Force Academy UNSW. "Local-global coupling in strategy games: extracting signatures and unfolding dynamics." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2008. http://handle.unsw.edu.au/1959.4/38723.
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Complexity underlying life is largely governed by the dynamics of interaction within and between living and nonliving entities. Evolutionary strategy games are extensively used in modelling and understanding complex behaviors in a wide range of fields including theoretical biology, social interactions, economics, politics, defense and security. Strategy games are said to distill the key elements of interactions be- tween real-world entities and organizations - one of the challenges lies in determining the mapping of complex real life situation dynamics to that of a certain game. That leads us to the two major research questions outlined below. In this thesis, we are taking evolutionary games a step further to investigate the interplay between local and global dynamics, where local dynamics are repre- sented by locally pairwise interactions among the population's players governed by the Iterated Prisoner's Dilemma game. To represent the global dynamics, two main modelling ideas are proposed, in the first model; a mixed evolutionary game is in- troduced where players are competing globally on the population level in a minority game. The interplay between local and global dynamics in this model represents the interplay between different scopes of competition between the same players. Sec- ondly, we introduce a model for studying the effect of sharing global information concerning a population of players, shedding light on how global information can alter the emerging dynamics of local interactions. Furthermore, the thesis addresses the question of whether games - with different dynamics - have unique signatures (footprints) that can be used in recognizing and differentiating among them, and whether these footprints are consistent along the evolutionary path of these games. We show here that by building winning networks between players, and determining network motifs of these winning networks, we can obtain motifs' counts signals that are sufficient to categorize and recognize the game's utility matrix used by the players. We also demonstrate that these footprints - motifs' counts - are consistent along the evolutionary path of the games, due to a hyper-cyclic behavior that exists between strategies. Finally, we show that this approach is capable of identifying whether a certain population is driven by local dynamics or both local and global dynamics using the proposed mixed game.
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Noeske, Niko [Verfasser]. "Exploring individual preferences in economic contexts: three essays in evolutionary game theory / Niko Noeske. Fakultät für Wirtschaftswissenschaften - Institut für mathematische Wirtschaftsforschung." Bielefeld : Universitätsbibliothek Bielefeld, Hochschulschriften, 2011. http://d-nb.info/1017712360/34.
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Intoy, Ben Frederick Martir. "Pure and Mixed Strategies in Cyclic Competition: Extinction, Coexistence, and Patterns." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/51999.
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We study game theoretic ecological models with cyclic competition in the case where the strategies can be mixed or pure. For both projects, reported in [49] and [50], we employ Monte Carlo simulations to study finite systems.
In chapter 3 the results of a previously published paper [49] are presented and expanded upon, where we study the extinction time of four cyclically competing species on different lattice structures using Lotka-Volterra dynamics. We find that the extinction time of a well mixed system goes linearly with respect to the system size and that the probability distribution approximately takes the shape of a shifted exponential. However, this is not true for when spatial structure is added to the model. In that case we find that instead the probability distribution takes on a non-trivial shape with two characteristic slopes and that the mean goes as a power law with an exponent greater than one. This is attributed to neutral species pairs, species who do not interact, forming domains and coarsening.
In chapter 4 the results of [50] are reported and expanded, where we allow agents to choose cyclically competing strategies out of a distribution. We first study the case of three strategies and find through both simulation and mean field equations that the probability distributions of the agents synchronize and oscillate with time in the limit where the agents probability distributions can be approximated as continuous. However, when we simulate the system on a one-dimensional lattice and the probability distributions are small and discretized, it is found that there is a drastic transition in stability, where the average extinction time of a strategy goes from being a power law with respect to system size to an exponential. This transition can also be observed in space time images with the emergence of tile patterns. We also look into the case of four cyclically competing strategies and find results similar to that of [49], such as the coarsening of neutral domains. However, the transition from power law to exponential for the average extinction time seen for three strategies is not observed, but we do find a transition from one power law to another with a different slope.
This work was supported by the United States National Science Foundation through grants DMR-0904999 and DMR-1205309.<br>Ph. D.
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Van, der Merwe Martijn. "Non-cooperative games on networks." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79930.
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Thesis (MSc)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: There are many examples of cooperation in action in society and in nature. In some cases
cooperation leads to the increase of the overall welfare of those involved, and in other cases
cooperation may be to the detriment of the larger society. The presence of cooperation seems
natural if there is a direct bene t to individuals who choose to cooperate. However, in examples
of cooperation this bene t is not always immediately obvious. The so called prisoner's
dilemma is often used as an analogy to study cooperation and tease out the factors that lead
to cooperation.
In classical game theory, each player is assumed to be rational and hence typically seeks to
select his strategy in such a way as to maximise his own expected pay-o . In the case of the
classical prisoner's dilemma, this causes both players to defect. In evolutionary game theory,
on the other hand, it is assumed that players have limited knowledge of the game and only
bounded rationality. Games in evolutionary game theory are repeated in rounds and players are
a orded the opportunity to adapt and learn as this repetition occurs. Past studies have revealed
that cooperation may be a viable strategy if the prisoner's dilemma is placed in an evolutionary
context, where the evolutionary tness of a strategy is directly related to the pay-o achieved
by the player adopting the strategy. One of the mechanisms that promote the persistence of
cooperation in the evolutionary prisoner's dilemma is structured interaction between players.
A mathematical framework for representing the evolutionary prisoner's dilemma (ESPD) is developed
in this thesis. The mathematical framework is used to undertake an analytical approach
(i.e. avoiding the use of simulation) towards investigating the dynamics of the ESPD with a
path, cycle, plane grid or toroidal grid as underlying graph. The objective of this investigation
is to determine the likelihood of the emergence of persistent cooperation between players. The
ESPD on a path or a cycle admits two fundamentally di erent parameter regions; large values
of the temptation-to-defect parameter are not capable of inducing persistent cooperation, while
small values of this parameter allow for the possibility of persistent cooperation. It is found that
the likelihood of cooperation increases towards certainty as the order of the underlying graph
increases if the underlying graph is a path or cycle.
The state space of the ESPD with a plane or toroidal grid graph as underlying graph grows
very quickly as a function of the graph order. The automorphism classes of game states are
enumerated to determine exactly how fast the size of the state space of the game grows as a
function of the order of the underlying graph. Finally, the dynamics of the ESPD is investigated
for a grid graph as underlying graph (in cases where the state space is small enough) by means
of constructing the corresponding state graphs of the ESPD.<br>AFRIKAANSE OPSOMMING: Daar is baie voorbeelde van samewerking in the gemeenskap en in die natuur. In sommige
gevalle lei samewerking tot 'n toename in die algehele welvaart van die betrokkenes, terwyl
samewerking in ander gevalle tot nadeel van die bre er gemeenskap mag wees. Die voorkoms van
samewerking blyk natuurlik te wees indien daar 'n direkte voordeel vir die individue is wat kies
om saam te werk. In voorbeelde van samewerking is s o 'n voordeel egter nie altyd voor-diehand-
liggend nie. Die sogenaamde prisoniersdilemma word dikwels as voorbeeld in die studie
van samewerking gebruik om die faktore wat na samewerking lei, te ontbloot.
In klassieke speleteorie word daar aangeneem dat elke speler rasioneel is en dus poog om sy
spelstrategie op s o 'n manier te kies dat sy eie verwagte uitbetaling gemaksimeer word. In die
geval van die klassieke prisoniersdilemma veroorsaak dit dat beide spelers mekaar verraai. In
evolusion^ere speleteorie, daarenteen, word daar slegs aangeneem dat elke speler oor beperkte
kennis van die spel en begrensde rasionaliteit beskik. Spele in evolusion^ere speleteorie word in
rondtes herhaal en spelers word die geleentheid gebied om gedurende hierdie herhalingsproses
aan te pas en te leer. Vorige studies het getoon dat samewerking 'n lewensvatbare strategie
is indien die prisoniersdilemma in 'n evolusion^ere konteks gespeel word, waar die evolusion^ere
ksheid van 'n strategie direk afhang van die uitbetaling van 'n speler wat die strategie volg.
Een van die meganismes wat volhoubare samewerking in die evolusion^ere prisoniersdilemma
voortbring, is gestruktureerde interaksie tussen spelers.
'n Wiskundige raamwerk word vir die voorstelling van die evolusion^ere prisoniersdilemma in
hierdie tesis ontwikkel. Hierdie wiskundige raamwerk word gebruik om 'n analitiese studie (met
ander woorde sonder die gebruik van simulasie) van die dinamika van die prisoniersdilemma op
'n pad, siklus, rooster in die vlak, of rooster op die torus as onderliggende gra ek van stapel te
stuur. Die doel van hierdie studie is om die waarskynlikheid vir die ontstaan van volhoubare
samewerking tussen spelers te bepaal. Die prisoniersdilemma op 'n pad of siklus as onderliggende
gra ek het twee fundamenteel verskillende parametergebiede tot gevolg; groot waardes van die
versoeking-om-te-verraai parameter lei nie tot volhoubare samewerking nie, terwyl volhoubare
samewerking wel vir klein waardes van hierdie parameter moontlik is. Daar word gevind dat die
kans vir volhoubare samewerking toeneem tot sekerheid namate die orde van die onderliggende
gra ek groei.
Die toestandsruimte van die prisoniersdilemma met 'n rooster in die vlak of 'n rooster op die
torus as onderliggende gra ek groei baie vinnig as 'n funksie van die orde van die gra ek. Die
outomor smeklasse van die speltoestande word getel met die doel om te bepaal presies hoe vinnig
die toestandsruimte van die spel as 'n funksie van die orde van die onderliggende gra ek groei.
Die dinamika van die prisoniersdilemma met 'n rooster in die vlak of 'n rooster op die torus
as onderliggende gra ek word laastens deur middel van konstruksies van die ooreenstemmende
toestandsgra eke ondersoek (in gevalle waar die toestandsruimte klein genoeg is).
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Driscoll, William Wallace. "Social and Asocial Niche Construction in Microbial Populations." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/228457.
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Cooperation presents a major challenge for evolutionary theory: how can competition favor a trait that imposes a cost on the individual expressing it while benefitting another? This challenge has been answered by theory that emphasizes the importance of assortment between individuals that tend to cooperate and those who tend to behave selfishly, or `cheat'. Microbial cooperation remains puzzling, given the generally high genetic and taxonomic diversity of most microbial communities. Many microbial populations rely on shared, beneficial extracellular products for an array of functions in nature. However, when these lineages are maintained in liquid cultures, many are invaded and outcompeted by spontaneous `cheater' mutants that forego investments in these products while benefitting from those produced by neighbors. The apparent evolutionary instability of microbial investments in extracellular products in well-mixed laboratory cultures finds a natural parallel in the phenomenon of toxic microalgal blooms. These extremely dense populations of often free-living microalgae destroy populations of competing microalgae and grazing zooplankton that normally control population densities. Bloom populations of planktonic microalgae are unstructured, and seem ill suited for the evolution of cooperation. In this thesis, I have established a new theoretical framework for understanding the evolution of microbial external goods. This framework highlights the importance of cell-level structure in the distribution of these external products, as well as genetic structuring in populations. This perspective informed an investigation into the social niche of a biofilm-dwelling regulatory mutant of the important biocontrol strain Pseudomonas chlororaphis. In the highly self-structured environment of a bacterial biofilm, a surprising mutualistic association between this mutant and the wild type emerged, underscoring the importance of microbial ecology in understanding the evolution of niche construction. Extending these lessons to the evolutionary problem of exotoxins in free-swimming microalgae yields the novel possibility that fluctuations in density of toxic strains shift a cell-level functioning exotoxin into a true public good that may be exploited by cheaters. I show that exotoxicity can serve cell-level functions in Prymnesium parvum. Despite these cell-level benefits, the existence of nontoxic lineages within toxic blooms hints at a complex interaction between rapid evolutionary and ecological changes in toxic blooms.
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Lee, Alexander. "The evolutionary ecology of animal information use and social dominance." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:1d2b343e-fe0a-4611-b1c7-b820da19e075.
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Organisms are frequently faced with uncertainty regarding how best to exploit vital resources, and may benefit from collecting information about their distribution through space and time. However, the ways in which competition over resources might systematically facilitate or constrain an individual's ability to use information has been largely overlooked. In this thesis, I develop a conceptual framework for considering how the distribution of limited resources might underpin interdependencies between competition and information use. I focus on the evolutionary ecology of relationships between social dominance and social information use. I begin with an observational study of wild chacma baboons (Papio ursinus) suggesting that, when resources can be monopolised, individuals with low competitive ability are limited in their ability to use social information. Building on these findings, I then develop a general model exploring selection on social information use in a competitive context across three axes of 'resource ecology' (scarcity, depletion rate, monopolisability). This study makes predictions regarding the resource conditions under which competitive ability might constrain social information use, and the potential importance of social information use in the evolution of social dominance. I go on to test these predictions in chacma baboons using a field experiment. This experiment also explores whether the predictability of resource distribution might facilitate the decoupling of social information use from the competitive context in which it was collected. Taken together, these findings provide general insights into the combinations of ecological conditions and behavioural mechanisms that should underpin the benefits of social dominance. I end by building a simple population matrix model to study social dominance using an eco-evolutionary approach, in which feedback loops between ecological and evolutionary processes are considered. By modelling relationships between dominance rank and survival, reproduction, inheritance, and development, I am able to derive estimates of long-term fitness associated with dominance. Using these estimates, I generate predictions regarding how dominance hierarchies should impact the dynamics of group stability, viability, and fission.
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Han, The Anh. "Intention recognition, commitment and their roles in the evolution of cooperation." Doctoral thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8784.
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Dissertação para obtenção do Grau de Doutor em
Informática<br>The goal of this thesis is twofold. First, intention recognition is studied from an
Arti cial Intelligence (AI) modeling perspective. We present a novel and e cient
intention recognition method that possesses several important features: (i) The
method is context-dependent and incremental, enabled by incrementally constructing
a three-layer Bayesian network model as more actions are observed, and in a
context-dependent manner, relying on a logic programming knowledge base concerning
the context; (ii) The Bayesian network is composed from a knowledge base
of readily speci ed and readily maintained Bayesian network fragments with simple
structures, enabling an e cient acquisition of the corresponding knowledge base (either
from domain experts or else automatically from a plan corpus); and, (iii) The
method addresses the issue of intention change and abandonment, and can appropriately
resolve the issue of multiple intentions recognition. Several aspects of the
method are evaluated experimentally, achieving some de nite success. Furthermore,
on top of the intention recognition method, a novel framework for intention-based
decision making is provided, illustrating several ways in which an ability to recognize
intentions of others can enhance a decision making process.
A second subgoal of the thesis concerns that, whereas intention recognition has
been extensively studied in small scale interactive settings, there is a major shortage
of modeling research with respect to large scale social contexts, namely evolutionary
roles and aspects of intention recognition. Employing our intention recognition
method and the tools of evolutionary game theory, this thesis explicitly addresses
the roles played by intention recognition in the nal outcome of cooperation in large
populations of self-regarding individuals. By equipping individuals with the capacity
for assessing intentions of others in the course of social dilemmas, we show how intention
recognition is selected by natural selection, opening a window of opportunity
for cooperation to thrive, even in hard cooperation prone games like the Prisoner's
Dilemma.
In addition, there are cases where it is di cult, if not impossible, to recognize the
intentions of another agent. In such cases, the strategy of proposing commitment,
or of intention manifestation, can help to impose or clarify the intentions of others. Again using the tools of evolutionary game theory, we show that a simple form of
commitment can lead to the emergence of cooperation; furthermore, the combination
of commitment with intention recognition leads to a strategy better than either one
by itself.
How the thesis should be read? We recommend that the thesis be read sequentially,
chapter by chapter [1-2-3-4-5-6-7-8].
However, for those more interested in intention recognition from the AI modeling
perspective, i.e. the rst subgoal of the thesis, Chapters 6 and 7 can be omitted and
Chapters 4 and 5 are optional [1-2-3-(4)-(5)-8].
In addition, for those more keen on the problem of the evolution of cooperation,
i.e. the second subgoal of thesis, Chapter 3 and even Chapter 2, can be omitted
[1-(2)-4-5-6-7-8].<br>Fundação para a Ciência e Tecnologia - PhD grant (ref. SFRH/BD/62373/2009)
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Fox, Michael Jacob. "Distributed learning in large populations." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44783.
Full textAbstract:
Distributed learning is the iterative process of decision-making in the presence of other decision-makers. In recent years, researchers across fields as disparate as engineering, biology, and economics have identified mathematically congruous problem formulations at the intersection of their disciplines. In particular, stochastic processes, game theory, and control theory have been brought to bare on certain very basic and universal questions. What sort of environments are conducive to distributed learning? Are there any generic algorithms offering non-trivial performance guarantees for a large class of models?
The first half of this thesis makes contributions to two particular problems in distributed learning, self-assembly and language. Self-assembly refers to the emergence of high-level structures via the aggregate behavior of simpler building blocks. A number of algorithms have been suggested that are capable of generic self-assembly of graphs. That is, given a description of the objective they produce a policy with a corresponding performance guarantee. These guarantees have been in the form of deterministic convergence results. We introduce the notion of stochastic stability to the self-assembly problem. The stochastically stable states are the configurations the system spends almost all of its time in as a noise parameter is taken to zero. We show that in this framework simple procedures exist that are capable of self-assembly of any tree under stringent locality constraints. Our procedure gives an asymptotically maximum yield of target assemblies while obeying communication and reversibility constraints. We also present a slightly more sophisticated algorithm that guarantees maximum yields for any problem size. The latter algorithm utilizes a somewhat more presumptive notion of agents' internal states. While it is unknown whether an algorithm providing maximum yields subject to our constraints can depend only on the more parsimonious form of internal state, we are able to show that such an algorithm would not be able to possess a unique completing rule--- a useful feature for analysis.
We then turn our attention to the problem of distributed learning of communication protocols, or, language. Recent results for signaling game models establish the non-negligible possibility of convergence, under distributed learning, to states of unbounded efficiency loss. We provide a tight lower bound on efficiency and discuss its implications. Moreover, motivated by the empirical phenomenon of linguistic drift, we study the signaling game under stochastic evolutionary dynamics. We again make use of stochastic stability analysis and show that the long-run distribution of states has support limited to the efficient communication systems. We find that this behavior is insensitive to the particular choice of evolutionary dynamic, a fact that is intuitively captured by the game's potential function corresponding to average fitness. Consequently, the model supports conclusions similar to those found in the literature on language competition. That is, we expect monomorphic language states to eventually predominate. Homophily has been identified as a feature that potentially stabilizes diverse linguistic communities. We find that incorporating homophily in our stochastic model gives mixed results. While the monomorphic prediction holds in the small noise limit, diversity can persist at higher noise levels or as a metastable phenomenon.
The contributions of the second half of this thesis relate to more basic issues in distributed learning. In particular, we provide new results on the problem of distributed convergence to Nash equilibrium in finite games. A recently proposed class of games known as stable games have the attractive property of admitting global convergence to equilibria under many learning dynamics. We show that stable games can be formulated as passive input-output systems. This observation enables us to identify passivity of a learning dynamic as a sufficient condition for global convergence in stable games. Notably, dynamics satisfying our condition need not exhibit positive correlation between the payoffs and their directions of motion. We show that our condition is satisfied by the dynamics known to exhibit global convergence in stable games. We give a decision-theoretic interpretation for passive learning dynamics that mirrors the interpretation of stable games as strategic environments exhibiting self-defeating externalities. Moreover, we exploit the flexibility of the passivity condition to study the impact of applying various forecasting heuristics to the payoffs used in the learning process. Finally, we show how passivity can be used to identify strategic tendencies of the players that allow for convergence in the presence of information lags of arbitrary duration in some games.
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RADI, Davide. "Essays on Nonlinear Dynamics, Heterogeneous Agents and Evolutionary Games in Economics and Finance." Doctoral thesis, Università degli studi di Bergamo, 2014. http://hdl.handle.net/10446/30390.
Full text
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Tavoni, Alessandro <1977>. "Essays on fairness heuristics and environmental dilemmas." Doctoral thesis, Università Ca' Foscari Venezia, 2010. http://hdl.handle.net/10579/1036.
Full textAbstract:
The issues explored in this work concern individual behaviour and its departure from the rationality paradigm. While different in terms of underlying methodology, the chapters share the unifying theme of
fairness as a guiding principle for human behaviour, as well as a focus on its relevance for environmental dilemmas.<br>Le questioni affrontate nella tesi riguardano i comportamenti individuali e i relativi scostamenti dal paradigma di razionalità. Nonostante l'utilizzo di metodologie diverse nei tre capitoli, essi hanno in comune il tema unificante di equità come principio guida del comportamento umano, così come una particolare attenzione alla sua rilevanza nei dilemmi ambientali.
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Søilen, Klaus Solberg. "Wirtschaftsspionage in Verhandlungen aus Informationsökonomischer und Wirtschaftsetischer Perspektive : eine Interdisziplinäre Analyse." Doctoral thesis, Karlskrona : Blekinge Institute of Technology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00295.
Full textAbstract:
The dissertation examines a case of industrial espionage by one of the parties involved in a forthcoming international negotiation. We want to know what consequences a burglary has for the actual negotiation. The dissertation consist of five hypothesis, of which the three first were empirically tested. The discussion of thesis four and five is supported basically by research literature, but have also found indirect support in the empirical study. A game theoretical model of four information sets is used. Thesis 1: Pay-offs do not change significantly from one information set to the other. confirmed Thesis 2: Behavior do not change significantly from one information set to the other. confirmed Thesis 3: The perception of fairness do not change significantly from one information set to the other. confirmed Thesis 4: International negotiations is socially so complex that it only makes sense to study the phenomena from an interdisciplinary angle. confirmed Thesis 5: A descriptive evolutionary approach can be an alternative to neoclassical economic theory in understanding the study of international negotiations. confirmed The study also confirms that economic theory is correct in excluding the ethical dimension from their models, as these factors have little influence on the end price. Fairness plays only a minor role in international negotiations. **<br><p>Forskarens hemsida: http://www.bth.se/iem/kss.nsf Disputerat vid Universität Leipzig, Wirtschaftswissenschaftliche Fakultät, http://www.uni-leipzig.de/ Avhandlingen utgiven av BTH.</p>
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Miller, Steven. "Network fluctuation as an explanatory factor in the evolution of cooperation." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/network-fluctuation-as-an-explanatory-factor-in-the-evolution-of-cooperation(56d08050-ce8d-408d-89b9-5cbe1f70f25d).html.
Full textAbstract:
Network reciprocity describes the emergence of cooperative behaviour where interactions are constrained by incomplete network connectivity. It has been widely studied as an enabling mechanism for the emergence of cooperation and may be of particular interest in explaining cooperative behaviours amongst unrelated individuals or in organisms of lower cognitive abilities. Research in this area has been galvanised by the finding that heterogeneous topology promotes cooperation. Consequently there has been a strong focus on scale-free networks; however, such networks typically presuppose formative mechanisms based on preferential attachment, a process which has no general explanation. This assumption may give rise to models of cooperation that implicitly encode capabilities only generally found in more complex forms of life, thus constraining their relevance with regards to the real world. By considering the connectivity of populations to be dynamic, rather than fixed, cooperation can exist at lower levels of heterogeneity. This thesis demonstrates that a model of network fluctuation, based on random rather than preferential growth, supports cooperative behaviour in simulated social networks of only moderate heterogeneity, thus overcoming difficulties associated with explanations based on scale-free networks. In addition to illustrating the emergence and persistence of cooperation in existing networks, we also demonstrate how cooperation may evolve in networks during their growth. In particular our model supports the emergence of cooperation in populations where it is originally absent. The combined impact of our findings increases the generality of reciprocity as an explanation for cooperation in networks.
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Koegler, Xavier. "Population protocols, games and large populations." Paris 7, 2012. http://www.theses.fr/2012PA077132.
Full textAbstract:
Le modèle des populations protocols a été proposé pour capturer les spécificités de réseaux opportunistes constitués d'une population d'agents mobiles à la mémoire limitée capables de communications sans fil par paires. L'objet de cette thèse est d'étendre la compréhension et l'analyse des population protocols ainsi que leurs liens avec d'autres modèles de dynamiques de populations. La première contribution de cette thèse est l'étude de la traduction en terme de protocoles de population de la dynamique d'une population d'agents jouant à un jeu de manière répétée les uns contre les autres et adaptant leur stratégie selon le comportement de PAVLOV. Nous montrons que les protocoles issus de tels jeux sont aussi puissants que les protocoles de population généraux. La deuxième contribution consiste à étudier des hypothèse de symétrie dans les jeux et dans les transitions d'un protocole de population, pour montrer que, si les protocoles de population symétriques sont équivalents aux protocoles généraux, les jeux symétriques sont, eux, significativement moins puissants. La troisième contribution est de montrer comment étudier le comportement d'une protocole de population lorsque la taille de la population tend vers l'infini en approchant la dynamique résultante à l'aide d'une équation différentielle ordinaire et de définir un calcul par grande population comme la convergence de cette équation différentielle vers un équilibre stable. La quatrième et dernière contribution de la thèse est la caractérisation des nombres calculables en ce sens comme étant très exactement les réels algébriques des [0,1]<br>Population protocols were introduced to capture the specifies of opportunistic networks of tny mobile agents with limited memory and capable of wireless communication in pairs. This thesis aims at extending the understanding and analysis of population protocols as well as their links to other models of population dynamics including ones from game theory. The first contribution of this thesis is to translate in terms of population protocols the dynamics of a population of agents playing a game repeatedly against each-other and adapting their strategy according to the PAVLOV behaviour. We show that protocols born from games are exactly as powerful as general population protocols. The second contribution consists in the study of the impact of symmetry on games and in the transitions of a population protocol to show that, if symmetric population protocols are equivalent to general protocols, symmetric games are significantly less powerful. The third contribution is to show how the dynamic of a population protocol can be approximated by an ordinary differential equation when the population grows to infinity. We then define a computation by a large population to be the convergence of this differential equation to a stable equilibrium. The fourth and final contribution of this thesis is the characterisation of the numbers computable in the above sense as exactly the algebraic real numbers in [0,1]
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Solberg, Søilen Klaus. "Wirtschaftsspionage in Verhandlungen aus Informationsökonomischer und Wirtschaftsetischer Perspektive : Eine Interdisziplinäre Analyse." Doctoral thesis, Blekinge Institute of Technology, School of Management, Karlskrona, Sweden, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-18032.
Full textAbstract:
The dissertation examines a case of industrial espionage by one of the parties involved in a forthcoming international negotiation. We want to know what consequences a burglary has for the actual negotiation. The dissertation consist of five hypothesis, of which the three first were empirically tested. The discussion of thesis four and five is supported basically by research literature, but have also found indirect support in the empirical study. A game theoretical model of four information sets is used.Thesis 1: Pay-offs do not change significantly from one information set to the other. confirmedThesis 2: Behavior do not change significantly from one information set to the other. confirmedThesis 3: The perception of fairness do not change significantly from one information set to the other. confirmedThesis 4: International negotiations is socially so complex that it only makes sense to study the phenomena from an interdisciplinary angle. confirmedThesis 5: A descriptive evolutionary approach can be an alternative to neoclassical economic theory in understanding the study of international negotiations. confirmedThe study also confirms that economic theory is correct in excluding the ethical dimension from their models, as these factors have little influence on the end price. Fairness plays only a minor role in international negotiations.
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De, Silva Hannelore, Christoph Hauert, Arne Traulsen, and Karl Sigmund. "Freedom, enforcement, and the social dilemma of strong altruism." Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/s00191-009-0162-8.
Full textAbstract:
Cooperation in joint enterprises poses a social dilemma. How can altruistic behavior be sustained if selfish alternatives provide a higher payoff? This social dilemma can be overcome by the threat of sanctions. But a sanctioning system is itself a public good and poses a second-order social dilemma. In this paper, we show by means of deterministic and stochastic evolutionary game theory that imitation-driven evolution can lead to the emergence of cooperation based on punishment, provided the participation in the joint enterprise is not compulsory. This surprising result - cooperation can be enforced if participation is voluntary - holds even in the case of 'strong altruism', when the benefits of a player's contribution are reaped by the other participants only. (authors' abstract)