OPIM 319, "Agents, Games & Evolution," explores applications and fundamentals of strategic behavior.
Strategic, or game-theoretic, topics arise throughout the social sciences. The topics include---and we shall study---trust, cooperation, market-related phenomena (including price equilibria and distribution of wealth), norms, conventions, commitment, coalition formation, and negotiation. They also include such applied matters as design of logistics systems, auctions, and markets generally (for example, markets for electric power generation).
In addressing these topics we focus on the practical problem of finding effective strategies for agents in strategic situations (or games). Our method of exploration will be experimental: we review and discuss experiments on the behavior of agents in strategic (or game-theoretic) situations.
In focusing on the design and behavior of artificial agents in strategic (or game-theoretic) situations, we will be especially concerned with strategic contexts of commercial import, such as markets, bargaining, and repeated play. We shall dwell on effective agent learning techniques, including evolutionary methods and reinforcement learning. A main theme in the course is the inherent difficulty, even unknowability, of the problem of strategy acquisition.
We will rely mainly on computational experiments (or simulations), in distinction to analytic mathematical methods, for studying strategy formation and strategic behavior (either by individuals or by groups). Much of the class work will be devoted to discussing and interpreting computational experiments that have been reported in the literature, or that can be undertaken with tools provided in class. In doing so, we draw upon the rapidly growing literature in agent-based modeling and agent-based simulation. Agent-Based Computational Economics (for example, http://www.econ.iastate.edu/tesfatsi/ace.htm) and Agent-Based Social Science (for example, http://www.brookings.edu/es/dynamics/papers/csed_wp41.htm) have come to denote active communities of research and application. We shall draw upon them.
Computer programming is neither required nor discouraged for the course. The instructor invites, and will support, projects using NetLogo (as well as other envirnments). Many of the computational demonstrations and experiments we will examine are available as NetLogo programs (http://ccl.northwestern.edu/netlogo/). Students are not, however, at all required to undertake programming exercises, in NetLogo or in any other environment.
Students completing the course can expect to come away with:
Class meets 3-4:30 p.m., Mondays and Wednesdays. Grading is based on class participation, assigned short essays undertaken during the term, a midterm quiz, and a term project. For further information, contact the principal instructor for the course, Professor Steven O. Kimbrough (kimbrough@wharton.upenn.edu).
See the class homepage http://opim-sun.wharton.upenn.edu/~sok/teaching/age/s06/ for further information.In addition, various other readings will be assigned. These will generally be handed out or made available online. In particular, we will read a number of chapters from Professor Kimbrough's draft manuscript, Agents, Games & Evolution, which is referred to below as the AGEbook.
Strategic interaction. Illustrations of "games in the wild." Towards a natural history of games. Read: "Contexts of Strategic Interaction," chapter 1 of AGEbook. Recommended reading: ``A Natural History of Peace,'' by Robert M. Sapolsky, Foreign Affairs, January/February 2006, Vol 85, Number 1. Link.
Read: "Micromotives and Macrobehavior," pp. 11-43 of Micromotives and Macrobehavior, Thomas C. Schelling, W.W. Norton & Co., New York, 1978.
Note: Schelling just (10 October 2005) won a Nobel Prize for doing this sort of work. http://nobelprize.org/economics/laureates/2005/press.html.Also read chapter 2 of the AGEbook, "Four Themes," and "The Tragedy of the Commons," by Garrett Hardin, Science, vol. 162, no. 3859, Dec. 13, 1968, pp. 1243-1248. PDF.
Games in strategic form, games in extensive form. Focus on 2×2 games. Equilibrium. Mixed equilibrium. Solution concepts. Folk Theorem. Read: "Games in the Abstract" chapter of AGE. Recommended reading: Wikipedia article on game theory: http://en.wikipedia.org/wiki/Game_theory. Recommended reading: Ross, Don "Game Theory", The Stanford Encyclopedia of Philosophy (Winter 2005 Edition), Edward N. Zalta (ed.), forthcoming URL = http://plato.stanford.edu/archives/win2005/entries/game-theory/, if it's available, otherwise: http://plato.stanford.edu/entries/game-theory/.
Read chapter 3 of the AGEbook.
Assignment 1 handed out.
Read: The Evolution of Cooperation by Robert Axelrod, Basic Books, 1984, chapters 1-3, appendix B.
Read: The Evolution of Cooperation by Robert Axelrod, Basic Books, 1984, chapters 4-5.
Read: The Evolution of Cooperation by Robert Axelrod, Basic Books, 1984, chapters 6-9 (skim).
Assignment 1 due.
Strategies that will be favored by evolution in repeated play of a game. Read: Wikipedia article on ESS: http://en.wikipedia.org/wiki/Evolutionarily_stable_strategy. Recommended reading: John Maynard Smith, "The Basic Model," chapter 2 (pp. 10-27) of Evolution and the Theory of Games, Cambridge University Press, 1982. Recommended reading: Alexander, J. McKenzie, "Evolutionary Game Theory", The Stanford Encyclopedia of Philosophy (Summer 2003 Edition), Edward N. Zalta (ed.), URL = http://plato.stanford.edu/archives/sum2003/entries/game-evolutionary/.
Assignment 2 (short essay) handed out.
Read: Brian Skyrms, Evolution of the Social Contract, chapters 1-2 ("Sex and Justice," pp. 1-21; "Commitment," pp. 22-44), Cambridge University Press, 1996.
Read: Brian Skyrms, The Stag Hunt and the Evolution of Social Structure, "Preface" (pp. xi-xiv) and chapter 1, "The Stag Hunt" (pp. 1-14), Cambridge University Press, 2004.
Assignment 3 (short essay) handed out.
Read: Brian Skyrms, The Stag Hunt and the Evolution of Social Structure, chapter 2, "Bargaining with Neighbors" (pp. 17-30) and chapter 3, "Stag Hunt with Neighbors" (pp. 31-44), Cambridge University Press, 2004.
Read: Brian Skyrms, The Stag Hunt and the Evolution of Social Structure, chapter 4, "Evolution of Inference" (pp. 45-64) and chapter 5, "Cheap Talk" (pp. 65-82), Cambridge University Press, 2004.
Read: Brian Skyrms, The Stag Hunt and the Evolution of Social Structure, chapter 6, "Choosing Partners" (pp. 87-104) and chapter 7, "Coevolution of Structure and Strategy" (pp. 105-124), Cambridge University Press, 2004.
Read: Garrett Hardin, "The Tragedy of the Commons," Science 162:1243-8, 1968. Read: Steven O. Kimbrough, "Foraging for Trust: Exploring Rationality and the Stag Hunt Game," in Trust Management: Third International Conference, iTrust 2005, Paris, France, May 23-26, 2005. Proceedings, P. Hermann, Valérie Issarny and Simon Shiu, eds., Springer-Verlag GmbH, Berlin, Germany, LNCS: Lecture Notes in Computer Science, 3477 / 2005, pp. 1-16, 2005. Read: Jon Elster, "Introduction: the two problems of social order," chapter 1 in The Cement of Society: A study of social order, Cambridge University Press, 1989, pp. 1-16.
Computational explorations of trust.
The Game of Life, among others. Read: "What Is Life?" in Winning Ways for Your Mathematical Plays, volume 2: Games in Particular, by Elwyn R. Berlekamp, John H. Conway and Richard K. Guy, Academic Press, 1982.
Read: Growing Artificial Societies: Social Science from the Bottom Up, by Joshua Epstein and Robert Axtell, MIT Press, 1996, chapters 1-2.
Read: Growing Artificial Societies: Social Science from the Bottom Up, by Joshua Epstein and Robert Axtell, MIT Press, 1996, chapters 3-4.
Read: Growing Artificial Societies: Social Science from the Bottom Up, by Joshua Epstein and Robert Axtell, MIT Press, 1996, chapters 5-6.
Computational demonstrations and experiments. Recommended readings: chapters from AGE.
Instructor handouts. Recommended reading: Patrick Grim, "Undecidability in the Spatialized Prisoner's Dilemma: Some Philosophical Implications" at http://www.sunysb.edu/philosophy/faculty/pgrim/SPATIALP.HTM
Read: Dhananjay K. Gode and Shyam Sunder, "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, 101, no. 1, pp. 119-137, 1993. File: gode-sunder-1993.pdf in misc. readings/ folder on webCafe.
Also read: J. Doyne Farmer and Andrew W. Lo, "Frontiers of finance: Evolution and efficient markets," Proceedings of the National Academy of Science, 96), pp. 9991-9992, August 1999. File: farmer-lo-1999.pdf in misc. readings/ folder on webCafe.
Recommended: Dhananjay K. Gode and Shyam Sunder, "What Makes Markets Allocationally Efficient?", The Quarterly Journal of Economics, 112, no. 2, May, 1997, pp. 603-630. File: gode-sunder-1997.pdf in misc. readings/ folder on webCafe.
Recommended: J. Doyne Farmer, Paolo Patelli, and Ilija I. Zovko, "The Predictive Power of Zero Intelligence in Financial Markets". File: farmer-etal-zi-2003.pdf in misc. readings/ folder on webCafe.
If time permits: Presentation of information regarding BehaviorSpace in NetLogo.
Read: D. Gale and L. S. Shapley, 1962. "College Admissions and the Stability of Marriage," The American Mathematical Monthly, 69, no. 1, pp. 9-15. Lawrence Bodin and Aaron Panken, 2003. "High Tech for a Higher Authority: The Place of Graduating Rabbis from Hebrew Union College--Jewish Institute of Religion," Interfaces, 33, no. 3, May-June, pp. 1-11.
Instructor handouts. Cournot duopoly models. Read: Steven O. Kimbrough, Ming Lu, and Frederic Murphy, 2004. "Learning and Tacit Collusion by Artificial Agents in Cournot Duopoly Games," in Steven O. Kimbrough and D. J. Wu, eds., Formal Modelling in Electronic Commerce, Springer, pp. 477-492.
Evolutionary computing. Genetic algorithms. Replicator dynamics. Genetic programming.
Evolutionary computing. Learning classifier systems. Models of individual learning in strategic contexts.
Summing up. Rationality redux.
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