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Relevant bibliographies by topics / Reinforcement Theory / Dissertations / Theses

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Dissertations / Theses on the topic 'Reinforcement Theory'

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Published: 4 June 2021

Last updated: 1 February 2022

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1

Hutchison, Ann Mechthild. "Reinforcement sensitivity theory, personality, and senior executive performance." Thesis, University of Auckland, 2010. http://hdl.handle.net/2292/6732.

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This thesis explores the extent to which Jeffrey Gray's reinforcement sensitivity theory of personality can predict and explain the job performance of top-level executive leaders. In this study, 189 senior executives underwent a battery of psychometric, biographical and performance measures. The dimensions of approach and avoidance motivation were measured using Carver and White's (1994) 'BIS/BAS Scales', and the predictive power of these dimensions was compared to R. Hogan and Hogan's (1997) ambition and adjustment traits. Overall, a model of senior executive performance prediction was

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2

Eftekhari, Zahra. "Preana: Game-theory Based Prediction with Reinforcement Learning." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1552.

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We have developed a game-theory based prediction tool, named Preana, based on a promising model developed by Professor Bruce Beuno de Mesquita. The first part of this work is dedicated to exploration of the specifics of Mesquita's algorithm and reproduction of the factors and features that have not been revealed in literature. In addition, we have developed a learning mechanism to model the players' reasoning ability when it comes to taking risks. Preana can predict the outcome of any issue with multiple stake-holders who have conflicting interests in economic, business, and political sciences

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3

Bonneau, Maxime. "Reinforcement Learning for 5G Handover." Thesis, Linköpings universitet, Statistik och maskininlärning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140816.

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The development of the 5G network is in progress, and one part of the process that needs to be optimised is the handover. This operation, consisting of changing the base station (BS) providing data to a user equipment (UE), needs to be efficient enough to be a seamless operation. From the BS point of view, this operation should be as economical as possible, while satisfying the UE needs. In this thesis, the problem of 5G handover has been addressed, and the chosen tool to solve this problem is reinforcement learning. A review of the different methods proposed by reinforcement learning led to

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4

Montag, Christian. "Die revidierte reinforcement sensitivity theory eine experimentell-biologische Überprüfung." Hamburg Kovač, 2008. http://d-nb.info/993570275/04.

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5

Mouton, Hildegarde Suzanne. "Reinforcement learning : theory, methods and application to decision support systems." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/5304.

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Thesis (MSc (Applied Mathematics))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: In this dissertation we study the machine learning subfield of Reinforcement Learning (RL). After developing a coherent background, we apply a Monte Carlo (MC) control algorithm with exploring starts (MCES), as well as an off-policy Temporal-Difference (TD) learning control algorithm, Q-learning, to a simplified version of the Weapon Assignment (WA) problem. For the MCES control algorithm, a discount parameter of τ = 1 is used. This gives very promising results when applied to 7 × 7 grids, as wel

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6

Keramati, Mohammadmahdi. "A homeostatic reinforcement learning theory, and its implications in cocaine addiction." Thesis, Paris 5, 2013. http://www.theses.fr/2013PA05T027/document.

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Cette thèse est composée de deux parties. Dans la première partie, nous proposons une théorie pour l'interaction entre l'apprentissage par renforcement et les processus de régulation homéostatique. En fait, la régulation efficace de l'homéostasie interne et la défendre contre les perturbations a besoin des stratégies comportementales complexes pour obtenir des ressources physiologiquement épuisés. À cet égard, il est essentiel que les processus cérébraux de régulation homéostatique et les processus d'apprentissage associatifs travaillent de concert. Nous proposons une théorie computationnelle

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7

Jurvelin, Olsson Mikael. "MULTI-AGENT REINFORCEMENT LEARNING WITH APPLICATION ON TRAFFIC FLOW CONTROL." Thesis, Uppsala universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447308.

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Traffic congestion diminish driving experience and increases the CO2 emissions. With the rise of 5G and machine learning, the possibilities to reduce traffic congestion are endless. This thesis aims to study if multi-agent reinforcement learning speed recommendations on a vehicle level can reduce congestion and thus control traffic flow. This is done by simulating a highway with an obstacle on one side of the lanes, forcing all the vehicles to drive on the same lane past the obstacle, resulting in congestion. A game theory aspect of drivers not obeying the speed recommendations was implemented

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8

Thrailkill, Eric A. "Token reinforcement and resistance to change." DigitalCommons@USU, 2013. http://digitalcommons.usu.edu/etd/1527.

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Interventions based on a token economy effectively reduce problematic behavior. Yet, treatment gains deteriorate once an intervention is discontinued. It is important to better understand the persistence of behavior maintained by token reinforcement in simple experimental procedures. A Pavlovian association with primary reinforcement is said to endow neutral stimuli (e.g., coins, poker chips, lights, signs, stickers, etc.) with their own function to strengthen behavior as conditioned reinforcers. Behavioral momentum theory suggests that resistance to change under conditions of disruption is th

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9

Liu, Chong. "Reinforcement learning with time perception." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/reinforcement-learning-with-time-perception(a03580bd-2dd6-4172-a061-90e8ac3022b8).html.

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Classical value estimation reinforcement learning algorithms do not perform very well in dynamic environments. On the other hand, the reinforcement learning of animals is quite flexible: they can adapt to dynamic environments very quickly and deal with noisy inputs very effectively. One feature that may contribute to animals' good performance in dynamic environments is that they learn and perceive the time to reward. In this research, we attempt to learn and perceive the time to reward and explore situations where the learned time information can be used to improve the performance of the learn

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10

Lindberg, Jesper. "Simulation driven reinforcement learning : Improving synthetic enemies in flight simulators." Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166593.

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This project focuses on how to implement an Artificial Intelligence (AI) -agent in a Tactical Simulator (Tacsi). Tacsi is a simulator used by Saab AB, one thing that the simulator is used for is pilot training. In this work, Tacsi will be used to simulate air to air combat. The agent uses Reinforcement Learning (RL) to be able to explore and learn how the simulator behaves. This knowledge will then be exploited when the agent tries to beat a computer-controlled synthetic enemy. The result of this study may be used to produce better synthetic enemies for pilot training. The RL-algorithm used in

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11

Mac, Dermed Liam Charles. "Value methods for efficiently solving stochastic games of complete and incomplete information." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50270.

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Multi-agent reinforcement learning (MARL) poses the same planning problem as traditional reinforcement learning (RL): What actions over time should an agent take in order to maximize its rewards? MARL tackles a challenging set of problems that can be better understood by modeling them as having a relatively simple environment but with complex dynamics attributed to the presence of other agents who are also attempting to maximize their rewards. A great wealth of research has developed around specific subsets of this problem, most notably when the rewards for each agent are either the same or di

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12

Kyureghian, Hrachya Henrik. "Theory and Simulations in Spatial Economics." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26077.

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Chapter 2 deals with a linear city model Ã la Hotelling where the two firms share linear transport costs with their customers. Mill pricing and uniform delivery pricing are special limiting cases. We characterize the conditions for the existence of a pure strategy equilibrium in the two-stage location-price game. These enable us to identify the causes for non-existence in the two limiting cases. We solve for the equilibrium of a location game between the duopolists with an exogenously given price. When the two firms are constrained to locate at the same central spot, we show the nonexistence

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13

Marriot, Shaun. "The application of adaptive resonance theory and reinforcement learning to mapping and control." Thesis, University of Sheffield, 1996. http://etheses.whiterose.ac.uk/5974/.

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In this thesis, the ideas of Adaptive Resonance Theory (ART) and Reinforcement Learning (RL) are applied to the problems of mapping and control. A neural architecture, fuzzy ARTMAP is considered as an alternative to standard feedforward networks for noisy mapping tasks. It is one of a series of architectures based upon ART. Fuzzy ARTMAP has advantages over feedforward networks--such as increased autonomy- and is especially suited to classification-type problems. Here it is used to estimate a continuous mapping from noisy data. Results show that properties useful for classification problems are

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14

Ritter, Samuel. "Meta-reinforcement Learning with Episodic Recall| An Integrative Theory of Reward-Driven Learning." Thesis, Princeton University, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13420812.

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<p> Research on reward-driven learning has produced and substantiated theories of model-free and model-based reinforcement learning (RL), which respectively explain how humans and animals learn reflexive habits and build prospective plans. A highly developed line of work has unearthed the role of striatal dopamine in model-free learning, while the prefrontal cortex (PFC) appears to critically subserve model-based learning. The recent theory of meta-reinforcement learning (meta-RL) explained a wide array of findings by positing that the model-free dopaminergic reward prediction error trains the

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Hutsell, Blake Allen. "Mechanics of Stimulus & Response Generalization in Signal Detection & Psychophysics: Adaptation of Static Theory to Dynamic Performance." OpenSIUC, 2009. https://opensiuc.lib.siu.edu/dissertations/98.

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The area of perceptual decision-making research seeks to understand how our perception of the world affects our judgment. Laboratory investigations of perceptual decision-making concentrate on observers' ability to discriminate among stimuli and their biases towards reporting one stimulus more frequently than others. Choice theories assume that these performance measures are determined by generalization of reinforcement along both stimulus and response dimensions. Historically the majority of research has addressed situations in which the difference among stimuli and resulting consequences of

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16

Fung, Sham. "Stochastic Game Theory Applications for Power Management in Cognitive Networks." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1398286269.

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17

Collins, Andrew. "Evaluating reinforcement learning for game theory application learning to price airline seats under competition." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/69751/.

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Applied Game Theory has been criticised for not being able to model real decision making situations. A game's sensitive nature and the difficultly in determining the utility payoff functions make it hard for a decision maker to rely upon any game theoretic results. Therefore the models tend to be simple due to the complexity of solving them (i.e. finding the equilibrium). In recent years, due to the increases of computing power, different computer modelling techniques have been applied in Game Theory. A major example is Artificial Intelligence methods e.g. Genetic Algorithms, Neural Networks a

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18

Liu, Jun Yong. "Modelling and control of united power flow controller for reinforcement of transmission systems." Thesis, Brunel University, 1997. http://bura.brunel.ac.uk/handle/2438/5225.

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The work involved in the thesis is concentrated on modelling and control of UPFC. The overall objective is to provide effective methods and tools for assessing the impact of UPFC in the reinforcement of transmission systems. The thesis clarifies modelling and control of UPFC into several subproblems, in which the associated models, algorithms and control strategies of UPFC have been systematically reviewed. An electromagnetic transient prototype model of the UPFC has been set up by using its detailed power electronic device as well as its internal closed-loop controller. The problems encounter

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19

Conradie, Alex van Eck. "Neurocontroller development for nonlinear processes utilising evolutionary reinforcement learning." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51841.

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Thesis (MEng)--University of Stellenbosch, 2000.<br>ENGLISH ABSTRACT: The growth in intelligent control has primarily been a reaction to the realisation that nonlinear control theory has been unable to provide practical solutions to present day control challenges. Consequently the chemical industry may be cited for numerous instances of overdesign, which result as an attempt to avoiding operation near or within complex (often more economically viable) operating regimes. Within these complex operating regimes robust control system performance may prove difficult to achieve using conventi

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Loxton, Natalie, and n/a. "The Contribution of Reinforcement Sensitivity Theory and Family Risk to Dysfuntional Eating and Hazardous Drinking." Griffith University. School of Applied Psychology, 2005. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20060112.111417.

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This thesis details a continuing body of research investigating the contribution of personality to disordered eating and alcohol abuse in young women. There is growing evidence of high levels of reward sensitivity in women with both disorders, and high levels of punishment sensitivity in dysfunctional eating women. However, it is unlikely that personality alone accounts for the development of such dysfunctional behaviour. Two studies were conducted to further examine the contribution of reward and punishment sensitivity to these disorders. In the first study, 443 university women completed sel

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21

Romani, Patrick William. "Relations between quality of reinforcement and the persistence of task completion." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/4736.

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Behavioral momentum theory (BMT) provides a theoretical framework for studying the persistence of behavior when challenged. The typical experimental arrangement to study persistence involves reinforcing a behavior according to a multiple schedules design. Unique schedules of reinforcement are programmed to each component. When steady-state responding occurs, the schedules of reinforcement are disrupted by a challenge condition (e.g., extinction, distraction, or prefeeding). The multiple schedules component that maintains the greatest level of responding during disruption is described as being

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22

Sather, Jonathon J. "Viewpoint Optimization for Autonomous Strawberry Harvesting with Deep Reinforcement Learning." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2008.

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Autonomous harvesting may provide a viable solution to mounting labor pressures in the United States' strawberry industry. However, due to bottlenecks in machine perception and economic viability, a profitable and commercially adopted strawberry harvesting system remains elusive. In this research, we explore the feasibility of using deep reinforcement learning to overcome these bottlenecks and develop a practical algorithm to address the sub-objective of viewpoint optimization, or the development of a control policy to direct a camera to favorable vantage points for autonomous harvesting. We e

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23

Kramer, Samuel Louis. "The Influence of Revised Reinforcement Sensitivity Theory Subsystems on Social Interaction and Social Observation Anxiety." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1429.

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Evidence suggests that both the BIS and the BAS play a role in the individual differences seen in social anxiety disorder; however, findings concerning the role of the BAS have been mixed. To date, the role of RST subsystems underlying social anxiety has been measured with outdated scales. This study addressed this issue by using a measure purpose-built for the revised RST. The current study was able to replicate past findings that the BAS is differentially related to social interaction anxiety and social observation anxiety (Kimbrel et al., 2010; Kimbrel et al., 2012). While using a newer mea

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Parisi, Aaron Thomas. "An Application of Sliding Mode Control to Model-Based Reinforcement Learning." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2054.

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The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have

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Kilmer, Jared Newman. "Reinforcement Sensitivity Theory and Proposed Personality Traits for the Dsm-v: Association with Mood Disorder Symptoms." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc271842/.

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The current work assesses the relationship between reinforcement sensitivity theory (RST) and Personality Traits for the DSM-5 (PID-5), to explore the degree to which they are associated with mood disorder symptoms. Participants (N = 138) from a large public university in the South were administered a semi-structured interview to assess for current mood disorder and anxiety symptoms. They were also administered self-report inventories, including the Behavioral Inhibition System (BIS) and Behavioral Approach System (BAS) scales and the Personality Inventory for DSM-5 (PID-5). Results indicate

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26

Boyce, Thomas E. "Effects of external contingencies on an actively caring behavior : a field test of intrinsic motivation theory /." Thesis, This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-01202010-020331/.

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27

Brauer, Jonathan Richard. "Examining the Empirical Status of Akers? Social Learning Theory: A Review of Literature on Human Reinforcement Learning." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-03192007-124842/.

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Proponents of social learning theory suggest that decades of empirical criminological research have validated the core propositions of social learning theory, and that future efforts should be directed toward further theoretical elaboration and integration (see Akers 1998; Akers and Jensen 2006). In response, some critics have suggested that empirical research has failed to isolate the causal mechanisms underlying the correlates of crime and deviance, and, as a result, existing ?data are seemingly consistent with several theories at once? (Sampson 1999:443). In this paper, I outline the causal

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Cone, Heather. "Differential Reinforcement in the Online Radicalization of Western Muslim Women Converts." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2962.

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The emerging phenomenon of Western women Islamic converts learning radicalized ideology through social media constitutes a challenge to cyber policy makers hampered by a lack of gender-nuanced radicalization research. The purpose of this exploratory qualitative case study was to develop a greater understanding of how the differential reinforcement tenet of social learning theory may help to explain the conversion and radicalization of Western women towards a fundamentalist Islamic ideology through their participation in the social media. Key research questions explored how participation in onl

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Døssland, Åse Lyslo. "Fibre Reinforcement in Load Carrying Concrete Structures : Laboratory and Field Investigations compared with Theory and Finite Element Analysis." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for konstruksjonsteknikk, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-2289.

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Fibre reinforcement can provide an alternative to conventional steel bars in order to improve the efficiency and working conditions on construction sites and in the prefabrication industry. Through the fibres ability to bridge cracks they improve the structural behaviour of the concrete by increased shear, moment and punching resistance, increased dowel effect, reduced crack spacing and crack widths, increased flexural stiffness and increased ductility in compression. A main reason for limited use of FRC in load-carrying structures seems to be the lack of accepted design guidelines. The princi

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Silguero, Russell V. "Do contingency-conflicting elements drop out of equivalence classes? Re-testing Sidman's (2000) theory." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc848078/.

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Sidman's (2000) theory of stimulus equivalence states that all positive elements in a reinforcement contingency enter an equivalence class. The theory also states that if an element from an equivalence class conflicts with a programmed reinforcement contingency, the conflicting element will drop out of the equivalence class. Minster et al. (2006) found evidence suggesting that a conflicting element does not drop out of an equivalence class. In an effort to explain maintained accuracy on programmed reinforcement contingencies, the authors seem to suggest that participants will behave in accorda

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Cora, Vlad M. "Model-based active learning in hierarchical policies." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/737.

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Hierarchical task decompositions play an essential role in the design of complex simulation and decision systems, such as the ones that arise in video games. Game designers find it very natural to adopt a divide-and-conquer philosophy of specifying hierarchical policies, where decision modules can be constructed somewhat independently. The process of choosing the parameters of these modules manually is typically lengthy and tedious. The hierarchical reinforcement learning (HRL) field has produced elegant ways of decomposing policies and value functions using semi-Markov decision processes. How

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Bailey, Kathleen. "The Effects of Cumulative Consumption Feedback On Demand For Money As A Commodity." Thesis, University of North Texas, 2001. https://digital.library.unt.edu/ark:/67531/metadc2823/.

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Behavioral economic theory describes a relation between response requirement and magnitude of reinforcement, and combines these variables into one independent variable (unit price) affecting operant behavior. This study investigated the relative effects of cumulative feedback on consumption for money as a commodity. Subjects were exposed to ranges of unit prices with or without a cumulative feedback bar on the computer screen indicating monetary earnings. For all participants in this study, consumption of money was a decreasing function of unit prices and the results from the present study are

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33

Dragone, David. "APPLYING MATCHING EQUATION TO PITCH SELECTION IN MAJOR LEAGUE BASEBALL." Master's thesis, Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/524832.

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Applied Behavioral Analysis<br>M.S.Ed.<br>This study applied the generalized matching equation (GME) to pitch selection in MLB during the 2016 regular season. The GME was used to evaluate the pitch selection of 21 groups of pitchers as well as 144 individual pitchers. The GME described pitch selection well for four of the 21 pitching groups and 32 of the 144 individual pitchers. Of the remaining groups and individual pitchers, behavior may be explained by rule following behavior or be impacted by distant reinforcers such as salary. All 21 groups demonstrated a bias for fastballs as well as 119

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34

Guerra, Roberto C. "The Role of Impulsivity and Reward Reactivity in Gray's Behavioral Activation System: Self-Reported Behavior and Autonomic Response to Reward." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/78076.

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The Behavioral Activation System (BAS) has been described as playing a central role in approach motivation and reward sensitivity (Gray, 1970). Self-report measures of BAS (e.g., Carver & White, 1994) have been used to index BAS activity, with higher scores interpreted as indicating greater BAS activity (e.g., Hundt et al., 2008). However, Beauchaine and colleagues (e.g., Brenner, Beauchaine, & Sylvers, 2005) have challenged this view, noting psychophysiological and neuroimaging evidence showing that externalizing behaviors are associated with reduced BAS functioning. Furthermore, global self-

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Zhang, Guohua. "Exploratory Robotic Controllers : An Evolution and Information Theory Driven Approach." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112208/document.

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Cette thèse porte sur la conception de contrôleurs pour robots explorateurs autonomes basée sur une approche en ligne (online) intégrée, ne nécessitant pas de vérité terrain ni d'intervention de l'expert humain au cours du processus d'entrainement.Le travail présenté se focalise sur le domaine de la robotique autonome et plus particulièrement la conception de controleurs robotiques pour les essaims de robots.Ce contexte présente deux difficultés spécifiques. Premièrement, les approches basées sur l'usage de simulateur sont d'efficacité limitée : d'une part, la précision du simulateur est limit

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Renner, Tracey Kimberly. "A theory of cross-pressures and reinforcement : the impact of presidential evaluations and party identification on voter turnout and choice in congressional elections /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Vance, Jonathan Blake. "Neural network control of nonstrict feedback and nonaffine nonlinear discrete-time systems with application to engine control." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Vance_09007dcc8043fb11.pdf.

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Thesis (Ph. D.)--University of Missouri--Rolla, 2007.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed March 26, 2008) Includes bibliographical references.

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Yin, Bo. "Airtime Management for Low-Latency Densely Deployed Wireless Networks." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263788.

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Konovalov, Arkady. "Essays in Behavioral Economics." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494436077382145.

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De, Pino Vincenzina, and enz79@hotmail com. "Reward Sensitivity and Outcome Expectancies Predict Both Alcohol and Cannabis Use in Young Adults." RMIT University. Health Sciences, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091020.101518.

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The primary focus of this thesis was to examine the relationship of reward sensitivity and outcome expectancies, variables traditionally associated with alcohol use, to cannabis use behaviour and to explore the relationship of affect and locus of control to alcohol and cannabis use. It was hypothesised that hazardous alcohol and cannabis use would be related to higher levels of reward sensitivity and to the endorsement of more positive outcome expectancies. It was also hypothesised that positive outcome expectancies would mediate the relationship between reward sensitivity and cannabis use,

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Xu, Dong. "An Integrated Simulation, Learning and Game-theoretic Framework for Supply Chain Competition." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/338942.

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An integrated simulation, learning, and game-theoretic framework is proposed to address the dynamics of supply chain competition. The proposed framework is composed of 1) simulation-based game platform, 2) game solving and analysis module, and 3) multi-agent reinforcement learning module. The simulation-based game platform supports multi-paradigm modeling, such as agent-based modeling, discrete-event simulation, and system dynamics modeling. The game solving and analysis module is designed to include various parts including strategy refinement, data sampling, game solving, equilibrium conditio

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Harder, Malte. "Information driven self-organization of agents and agent collectives." Thesis, University of Hertfordshire, 2014. http://hdl.handle.net/2299/13907.

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From a visual standpoint it is often easy to point out whether a system is considered to be self-organizing or not, though a quantitative approach would be more helpful. Information theory, as introduced by Shannon, provides the right tools not only quantify self-organization, but also to investigate it in relation to the information processing performed by individual agents within a collective. This thesis sets out to introduce methods to quantify spatial self-organization in collective systems in the continuous domain as a means to investigate morphogenetic processes. In biology, morphogenes

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Strandell, Pontus. "Motivation från personliga tränares perspektiv : Hur inre och yttre motivation rymmer sig inom yrket som personlig tränare." Thesis, Karlstads universitet, Institutionen för hälsovetenskaper, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43792.

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Den här studien behandlar personliga tränares arbete med inre och yttre motivation. Syftet är att undersöka hur personliga tränare arbetar med dessa motivationsinriktningar samt hur motivation kan gestalta sig hos deras klienter - för att i slutändan kunna presentera den inriktningen som är mest gynnsam för klientens långsiktiga upprätthållning av ett beteende. för att undersöka frågeställningar användes semi-strukturerade intervjuer. Inre motivatorer som identifierades var vilja, ambition och intresse. Yttre motivatorer som identifierades var förväntningar och press från omgivningen, tränarpr

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Li, Jun. "Learning Average Reward Irreducible Stochastic Games: Analysis and Applications." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000136.

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Roper, Zachary Joseph Jackson. "The manifold role of reward value on visual attention." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/2005.

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The environment is abundant with visual information. Each moment, this information competes for representation in the brain. From billboards and pop-up ads to smart phones and flat screens, in modern society our attention is constantly drawn from one salient object to the next. Learning how to focus on the objects that are most important for the current task is a major developmental hurdle. Fortunately, rewards help us to learn what is important by providing feedback signals to the brain. Sometimes,

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Chalk, Daniel. "Artificially intelligent foraging." Thesis, University of Exeter, 2009. http://hdl.handle.net/10036/96455.

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Bumble bees (bombus spp.) are significant pollinators of many plants, and are particularly attracted to mass-flowering crops such as Oilseed Rape (Brassica Napus), which they cross-pollinate. B. napus is both wind and insect-pollinated, and whilst it has been found that wind is its most significant pollen vector, the influence of bumble bee pollination could be non-trivial when bee densities are large. Therefore, the assessment of pollinator-mediated cross-pollination events could be important when considering containment strategies of genetically modified (GM) crops, such as GM varieties of B

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Schlesinger, Carla M., and n/a. "The Role of Individual Differences in Additional Substance Use in a Methadone Maintained Population." Griffith University. School of Psychology, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20061109.150823.

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It is well established that methadone maintenance (MM) reduces but does not eliminate the self-administration of other illicit drugs. For those on MM, there is considerable variation in consumption patterns, route of heroin administration, additional non-opioid substances routinely administered and the clinical disorders associated with these patterns of use. While there is a large literature base documenting these phenomena, studies have been almost exclusively descriptive in nature, with little attempt to develop a theoretical model in which to understand such use. In the following thesis, a

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Foss, Erica K. "An Evaluation of the Effects of Effort on Resistance to Change." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc955092/.

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Behavioral momentum theory (BMT) has become a prominent method of studying the effects of reinforcement on operant behavior. BMT represents a departure from the Skinnerian tradition in that it identifies the strength of responding with its resistance to change. Like in many other operant research paradigms, however, responses are considered to be momentary phenomena and so little attention has been paid to non-rate dimensions of responding. The current study takes up the question of whether or not the degree of effort defining a discriminated operant class has any meaningful effect on its resi

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Bountourelis, Theologos. "Efficient pac-learning for episodic tasks with acyclic state spaces and the optimal node visitation problem in acyclic stochastic digaphs." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28144.

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Thesis (M. S.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Reveliotis, Spyros; Committee Member: Ayhan, Hayriye; Committee Member: Goldsman, Dave; Committee Member: Shamma, Jeff; Committee Member: Zwart, Bert.

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Elbamby, M. S. (Mohammed S. ). "Flexible duplexing and resource optimization in small cell networks." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526224640.

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Abstract The next-generation networks are set to support a high data rate, low latency, high reliability, and diverse types of services and use cases. These requirements come at the expense of a more complex network management, and asymmetric and time-varying traffic dynamics. Accordingly, future networks will operate at different duplexing modes and with multiple access techniques. This thesis proposes novel transmission strategies and methodologies to dynamically optimize the duplexing modes and allocate resources for small cell based cellular networks. The first part of the thesis studies d

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