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Articoli di riviste sul tema "Game theory"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 9 giugno 2025

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1

M. Ferreira, Manuel Alberto, and Maria Cristina Peixoto Matos. "Game theory and coopetition." Journal of Economics and Engineering 5, no. 1 (April 30, 2014): 5–8. http://dx.doi.org/10.7813/jee.2014/5-1/1.

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2

Hanley, John T. "GAMES, game theory and artificial intelligence." Journal of Defense Analytics and Logistics 5, no. 2 (December 7, 2021): 114–30. http://dx.doi.org/10.1108/jdal-10-2021-0011.

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PurposeThe purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.Design/methodology/approachThe approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.FindingsGame theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.Originality/valueThough games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.

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3

Goodwin, Paul. "Forecasting games: can game theory win?" International Journal of Forecasting 18, no. 3 (July 2002): 369–74. http://dx.doi.org/10.1016/s0169-2070(02)00022-5.

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4

Olsder, Geert Jan. "Foundations of game theory: Noncooperative games." Automatica 32, no. 9 (September 1996): 1341–42. http://dx.doi.org/10.1016/0005-1098(96)88873-x.

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5

Taylor, Mark, Mike Baskett, Denis Reilly, and Somasundaram Ravindran. "Game Theory for Computer Games Design." Games and Culture 14, no. 7-8 (November 12, 2017): 843–55. http://dx.doi.org/10.1177/1555412017740497.

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Designing and developing computer games can be a complex activity that may involve professionals from a variety of disciplines. In this article, we examine the use of game theory for supporting the design of gameplay within the different sections of a computer game and demonstrate its application in practice via adapted high-level decision trees for modeling the flow in gameplay and payoff matrices for modeling skill or challenge levels.

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6

Fudenberg, Drew, and David K. Levine. "Whither Game Theory? Towards a Theory of Learning in Games." Journal of Economic Perspectives 30, no. 4 (November 1, 2016): 151–70. http://dx.doi.org/10.1257/jep.30.4.151.

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Game theory has been a huge success in economics. Many important questions have been answered, and game theoretic methods are now central to much economic investigation. We suggest areas where further advances are important, and argue that models of learning are a promising route for improving and widening game theory's predictive power while preserving the successes of game theory where it already works well. We emphasize in particular the need for better understanding of the speed with which learning takes place.

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7

Coffey, Aodhan L., Tomas E. Ward, and Richard H. Middleton. "Game Theory." International Journal of Ambient Computing and Intelligence 3, no. 3 (July 2011): 43–51. http://dx.doi.org/10.4018/jaci.2011070106.

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Designing suitable robotic controllers for automating movement-based rehabilitation therapy requires an understanding of the interaction between patient and therapist. Current approaches do not take into account the highly dynamic and interdependent nature of this relationship. A better understanding can be accomplished through framing the interaction as a problem in game theory. The main strength behind this approach is the potential to develop robotic control systems which automatically adapt to patient interaction behavior. Agents learn from experiences, and adapt their behaviors so they are better suited to their environment. As the models evolve, structures, patterns and behaviors emerge that were not explicitly programmed into the original models, but which instead surface through the agent interactions with each other and their environment. This paper advocates the use of such agent based models for analysing patient-therapist interactions with a view to designing more efficient and effective robotic controllers for automated therapeutic intervention in motor rehabilitation. The authors demonstrate in a simplified implementation the effectiveness of this approach through simulating known behavioral patterns observed in real patient-therapist interactions, such as learned dependency.

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8

Rubinstein, Ariel, Drew Fudenberg, and Jean Tirole. "Game Theory." Economica 60, no. 238 (May 1993): 245. http://dx.doi.org/10.2307/2554596.

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9

Eichberger, Jurgen, Drew Fudenberg, Jean Tirole, and Roger B. Myerson. "Game Theory." Economic Journal 103, no. 419 (July 1993): 1065. http://dx.doi.org/10.2307/2234726.

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10

Paturel, Amy. "Game Theory." Neurology Now 10, no. 3 (2014): 32–36. http://dx.doi.org/10.1097/01.nnn.0000451325.82915.1d.

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11

Prasad, Kislaya. "Game theory." International Review of Economics & Finance 3, no. 1 (January 1994): 129–31. http://dx.doi.org/10.1016/1059-0560(94)90048-5.

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12

Wilson, Charles A. "Game theory." Games and Economic Behavior 4, no. 2 (April 1992): 314–17. http://dx.doi.org/10.1016/0899-8256(92)90021-j.

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13

Dufwenberg, Martin. "Game theory." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 2 (October 15, 2010): 167–73. http://dx.doi.org/10.1002/wcs.119.

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14

Babu, P. G. "Game theory." Resonance 3, no. 7 (July 1998): 53–60. http://dx.doi.org/10.1007/bf02837313.

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15

Babu, P. G. "Game theory." Resonance 3, no. 8 (August 1998): 46–55. http://dx.doi.org/10.1007/bf02837345.

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16

Cossins, Daniel. "Game theory." New Scientist 228, no. 3051 (December 2015): 36. http://dx.doi.org/10.1016/s0262-4079(15)31762-0.

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17

Britten, Anna. "Game theory." Significance 20, no. 6 (December 1, 2023): 34–35. http://dx.doi.org/10.1093/jrssig/qmad096.

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Abstract Looking for some new games to beat family and friends at this Christmas? Marcus du Sautoy’s new book gathers traditional games from around the world, explores the maths embedded in them and shows us what they reveal about our species

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18

Fudenberg, D., and D. K. Levine. "Whither game theory? Towards a theory oflearning in games." Voprosy Ekonomiki, no. 5 (May 20, 2017): 116–35. http://dx.doi.org/10.32609/0042-8736-2017-5-116-135.

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Теория игр достигла необыкновенных успехов в рамках экономической науки. Были получены ответы на многие важные вопросы, теоретико-игровые методы теперь играют ключевую роль в экономических исследованиях. В статье показано, в каких областях необходимы дальнейшие изыскания. Утверждается, что модели обучения позволят усовершенствовать и расширить предсказательную силу теории игр, сохранив имеющиеся успешные приложения. Особый акцент сделан на необходимости точнее исследовать скорость обучения.

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19

Brams, Steven J. "Game Theory and Literature." Games and Economic Behavior 6, no. 1 (January 1994): 32–54. http://dx.doi.org/10.1006/game.1994.1002.

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20

Glynatsi, Nikoleta, and Vincent Knight. "Game Theory and Python: An educational tutorial to game theory and repeated games using Python." Journal of Open Source Education 4, no. 39 (May 24, 2021): 78. http://dx.doi.org/10.21105/jose.00078.

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21

Pi, Jiasheng. "Game Theory and Game Mechanics Design." SHS Web of Conferences 188 (2024): 03020. http://dx.doi.org/10.1051/shsconf/202418803020.

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This paper focuses on the significance of game balance in games and explores the application of game theory concepts for designing and analyzing balanced gameplay. When analyzing instances of games, the paper initially presents the renowned prisoner’s dilemma, a prominent problem in game theory, and delves into diverse strategies along with their corresponding advantages, thereby enabling readers to appreciate the captivating essence of game theory. After that, the paper respectively mentions two individual cases from two different forms of games. The well-known game Rock-Paper-Scissors is a simple strategy game. FPS (First Person Shooter) game is a sort of video game that is a complex strategy game. In analyzing this type of game, the paper draws images to show the imbalance in the game. In the end, the article puts forward the prospect that game theory can contribute to game design. The approach adopted in this study integrates existing research in game theory with practical insights from game design, without delving into extensive theoretical derivations or complex formulas.

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22

Wu, Wentao. "Theory and Practical Application Based on Game Theory." BCP Business & Management 44 (April 27, 2023): 919–25. http://dx.doi.org/10.54691/bcpbm.v44i.4978.

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Game theory refers to the method in which one of the interacting parties obtains the decision-making information of the other party and uses it to influence the other party in turn. Therefore, game theory is also called "game theory". Game theory can be divided into cooperative game and non-cooperative game. In recent decades, the theory of game theory has developed rapidly with the establishment of John Nash and has been applied to many fields such as medical, engineering, military, and business. In this paper, the author starts from the basic definition of game theory and analyze the prisoner's dilemma, concordance fallacy, median voter theorem, Gounod model, Bertrand model, iterative deletion of dominated strategy, etc. through specific cases. The research results show that game theory has been widely used in the economy. For bilateral games, the results of Nash equilibrium are unstable. The research in this paper broadens the theory of game theory and has important practical significance for the application research of game theory.

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23

Ray, Indrajit, and Lin Zhou. "Game Theory via Revealed Preferences." Games and Economic Behavior 37, no. 2 (November 2001): 415–24. http://dx.doi.org/10.1006/game.2001.0845.

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24

Crogan, Patrick. "The Game Thing: Ludology and other Theory Games." Media International Australia 110, no. 1 (February 2004): 10–18. http://dx.doi.org/10.1177/1329878x0411000104.

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The current state of computer games studies is critically examined in this paper by means of an analysis of the recently released computer game, The Thing. Game studies is an emerging area of humanities scholarship, an emergence that exhibits characteristically ambivalent processes of defining its own object and staking out its own field of expertise from other areas of academic competence. A principal dynamic of these processes concerns the opposition between ‘ludological’ and narratological theorisations of the computer game. This opposition is examined for both its limitations and its productive potential by means of consideration of The Thing game and its relation to John Carpenter's cinematic iteration of the original short story from which it is adapted. This consideration leads away from the question of the specificity of the computer game object to some concluding speculations about the relation of contemporary computer games to the broader computer culture within which games are taking on an increasingly significant profile.

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25

Wasow, Thomas. "Binding theory meets game theory." Semiotica 98, no. 1-2 (September 1, 1994): 187–98. http://dx.doi.org/10.1515/semi-1994-981-211.

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26

Khouzani, MHR, and Pasquale Malacaria. "Information Theory in Game Theory." Entropy 20, no. 11 (October 24, 2018): 817. http://dx.doi.org/10.3390/e20110817.

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Information theory, as the mathematics of communication and storage of information, and game theory, as the mathematics of adversarial and cooperative strategic behaviour, are each successful fields of research on their own. [...]

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27

Serhii, Yevseiev, Milov Oleksandr, Milevskyi Stanislav, Voitko Oleksandr, Kasianenko Maksym, Melenti Yevgen, Pohasii Serhii, Stepanov Hrygorii, Turinskyi Oleksandr, and Faraon Serhii. "DEVELOPMENT AND ANALYSIS OF GAME-THEORETICAL MODELS OF SECURITY SYSTEMS AGENTS INTERACTION." Eastern-European Journal of Enterprise Technologies 2, no. 4 (104) (April 30, 2020): 15–29. https://doi.org/10.15587/1729-4061.2020.201418.

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A game-theoretic approach is presented, which claims to be a universal method for solving most problems in the field of cybersecurity. As arguments to confirm the superiority of game theory, mathematical validity and provability of the optimality of decisions made, unlike the widely used heuristics, the possibility of developing reliable protection based on analytical results, ensuring a timely response to cyberattacks in conditions of limited resources, as well as distributed nature of decision making are highlighted. The definitions of the basic concepts used in security tasks based on game-theoretic models are introduced. The features of the application of game theory methods in the field of cybersecurity are listed and the limitations of research in this area are formulated, namely: a restriction on game strategies, simultaneous moves of players in the behavior patterns of security system agents, uncertainty in the time the players take the move, uncertainty in the final goal of the enemy, unpredictability of further player moves, lack of players’ assessment of enemy resources. as well as its ultimate goals, the inability to timely assess the current state of the game. The game-theoretic models are aligned with the listed security problems, and the main solutions obtained as a result of using the corresponding models are also determined. Many methods of game theory have been formed, for each of which a relationship is determined between the game model, its scope, simulation result and security services that the method under consideration supports. The limitations of the classical representation of game theory models are determined, the need to overcome which follows from the requirements for providing basic security services. Such limitations include: the ability of the defender to detect attacks, the certainty of the probabilities of a change of state before the start of the game, the synchronism of the players’ moves, the inability to scale the model due to the size and complexity of the system under consideration. Models of the main tasks of the interaction of antagonistic agents of security systems have been developed. The resulting models made it possible to obtain solutions to two of the most common tasks in the field of cybersecurity, namely, the interaction of the system administrator and the attacker in organizing the protection of information resources. The tasks are solved for various conditions – the game matrix contains cost estimates of resources and the matrix reflects the probability of threat realization. Pure and mixed strategies are defined for various initial conditions, which allows to exclude from the consideration strategies that are not included in the solution. A synergistic approach to the use of game-theoretic modeling was formed taking into account the behavior of agents of security systems, based on an analysis of the diversity and characteristics of game-theoretic models, their inherent limitations and scope

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28

Michel, Arij. "Evolutionary Game Theory." International Journal of Circular Economy and Waste Management 1, no. 2 (July 2021): 20–28. http://dx.doi.org/10.4018/ijcewm.2021070103.

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The article uses evolutionary game theory analysis as the research object, which is the most commonly used research method of institutional change, and summarizes some methods in the research of institutional change, and points out the advantages and disadvantages of evolutionary game analysis in the research of institutional change and through the comparison of cutting-edge methods and evolutionary games to see the development direction of future research institutional changes.

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29

Ortmann, Andreas, and Jorgen W. Weibull. "Evolutionary Game Theory." Southern Economic Journal 63, no. 3 (January 1997): 834. http://dx.doi.org/10.2307/1061129.

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30

Hopkins, Ed. "Evolving Game Theory." Journal of Economic Surveys 11, no. 1 (March 1997): 101–6. http://dx.doi.org/10.1111/1467-6419.00025.

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31

Fudenberg, Drew, Jörgen W. Weibull, and Jorgen W. Weibull. "Evolutionary Game Theory." Scandinavian Journal of Economics 98, no. 3 (September 1996): 461. http://dx.doi.org/10.2307/3440739.

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32

Munro, Alistair. "Evolutionary Game Theory." Economic Journal 107, no. 440 (January 1, 1997): 218–19. http://dx.doi.org/10.1093/ej/107.440.218.

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33

Krueger, Joachim I. "Heuristic game theory." Decision 1, no. 1 (2014): 59–61. http://dx.doi.org/10.1037/dec0000002.

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34

Kline, J. Jude. "Basic Game Theory." Australian Economic Review 33, no. 4 (December 2000): 381–87. http://dx.doi.org/10.1111/1467-8462.00170.

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35

RAPOPORT, ANATOL. "Game Theory Defined." Rationality and Society 4, no. 1 (January 1992): 74–82. http://dx.doi.org/10.1177/1043463192004001009.

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36

Roughgarden, Tim. "Algorithmic game theory." Communications of the ACM 53, no. 7 (July 2010): 78–86. http://dx.doi.org/10.1145/1785414.1785439.

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37

Sigmund, Karl, and Martin A. Nowak. "Evolutionary game theory." Current Biology 9, no. 14 (July 1999): R503—R505. http://dx.doi.org/10.1016/s0960-9822(99)80321-2.

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38

Aghassi, Michele, and Dimitris Bertsimas. "Robust game theory." Mathematical Programming 107, no. 1-2 (February 2, 2006): 231–73. http://dx.doi.org/10.1007/s10107-005-0686-0.

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39

Smith, John Maynard. "Evolutionary game theory." Physica D: Nonlinear Phenomena 22, no. 1-3 (October 1986): 43–49. http://dx.doi.org/10.1016/0167-2789(86)90232-0.

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40

Velegol, Darrell, Paul Suhey, John Connolly, Natalie Morrissey, and Laura Cook. "Chemical Game Theory." Industrial & Engineering Chemistry Research 57, no. 41 (September 14, 2018): 13593–607. http://dx.doi.org/10.1021/acs.iecr.8b03835.

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41

Van Damme, Eric. "Evolutionary game theory." European Economic Review 38, no. 3-4 (April 1994): 847–58. http://dx.doi.org/10.1016/0014-2921(94)90121-x.

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42

Illius, Andrew. "Big-game theory." Nature 429, no. 6991 (June 2004): 504–5. http://dx.doi.org/10.1038/429504a.

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43

Hausman, Daniel M. "‘Testing’ game theory." Journal of Economic Methodology 12, no. 2 (June 2005): 211–23. http://dx.doi.org/10.1080/13501780500086065.

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44

Richter, Michael, and Ariel Rubinstein. "Holding a Group Together: Non-Game Theory Versus Game Theory." Economic Journal 131, no. 638 (March 26, 2021): 2629–41. http://dx.doi.org/10.1093/ej/ueab026.

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Abstract Each member of a group chooses a position and has preferences regarding his chosen position. The group’s harmony depends on the profile of chosen positions meeting a specific condition. We analyse a solution concept (Richter and Rubinstein, 2020) based on a permissible set of individual positions, which plays a role analogous to that of prices in competitive equilibrium. Given the permissible set, members choose their most preferred position. The set is tightened if the chosen positions are inharmonious and relaxed if the restrictions are unnecessary. This new equilibrium concept yields more attractive outcomes than does Nash equilibrium in the corresponding game.

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Goeree, J. K., and C. A. Holt. "Stochastic game theory: For playing games, not just for doing theory." Proceedings of the National Academy of Sciences 96, no. 19 (September 14, 1999): 10564–67. http://dx.doi.org/10.1073/pnas.96.19.10564.

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46

Bellany, Ian. "Superpower games: applying game theory to superpower conflict." International Affairs 62, no. 3 (1986): 511. http://dx.doi.org/10.2307/2617909.

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Bever, Kerstin, and Julie Rowlett. "Love Games: A Game-Theory Approach To Compatibility." Journal of Humanistic Mathematics 5, no. 1 (January 2015): 82–104. http://dx.doi.org/10.5642/jhummath.201501.05.

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48

Becking, Bob. "Biblical Games: Game Theory and the Hebrew Bible." Ars Disputandi 3, no. 1 (January 2003): 91–93. http://dx.doi.org/10.1080/15665399.2003.10819770.

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49

Akiyama, E., and K. Kaneko. "Dynamical systems game theory and dynamics of games." Physica D: Nonlinear Phenomena 147, no. 3-4 (December 2000): 221–58. http://dx.doi.org/10.1016/s0167-2789(00)00157-3.

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Charron, William. "Greeks and games: Forerunners of modern game theory." Forum for Social Economics 29, no. 2 (January 2000): 1–32. http://dx.doi.org/10.1007/bf02779101.

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