Game theory and artificial intelligence

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2403, Issue , 2002, Pages 49-58

  Tennenholtz, Moshe ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT AGENTS; MULTI AGENT SYSTEMS;

RECENT RESEARCHES;

GAME THEORY;

EID: 84942813616     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45634-1_4     Document Type: Conference Paper

References (19)

1. Allan Borodin and Ran El-Yaniv. On-Line Computation and Competitive Analysis. Cambridge University Press, 1998.
2. C. Boutilier, T. Dean, and S. Hanks. Decision Theoretic Planning: Structural Assumptions and Computational Leverage. Journal of Artificial Intelligence Research, 11:1-94, 1999.
3. R. Brafman and M. Tennenholtz. R-max - AGeneral Polynomial Time Algorithm for Near-Optimal Reinforcement Learning. In Proc. of the 17th International Joint Conference on Artificial Intelligence, pages 953-958, 2001.
4. R. I. Brafman and M. Tennenholtz. An axiomatic treatment of three qualitative decision criteria. Journal of the ACM, 47(3), March 2000.
5. E. Clarke. Multipart pricing of public goods. Public Choice, 18:19-33, 1971.
6. I. Erev and A.E. Roth. Predicting how people play games: Reinforcement learning in games with unique strategy equilibrium. American Economic Review, 88:848-881, 1998.
7. R. Fagin, J. Y. Halpern, Y. Moses, and M. Y. Vardi. Reasoning about Knowledge. MIT Press, 1995.
8. D. Fudenberg and D. Levine. The theory of learning in games. MIT Press, 1998.
9. L. P. Kaelbling, M. L. Littman, and A. W. Moore. Reinforcement learning: A survey. Journal of AI Research, 4:237-285, 1996.
10. S. Kraus. Negotiation and cooperation in multi-agent environments. Artificial Intelligence, 94:79-97, 1997.
11. A. Neyman. Bounded complexity justifies cooperation in the infinitely repeated prisoner’s dilemma. Econ. Lett., 19:227-229, 1985.
12. M.L. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, 1994.
13. Holzman R, Noa Kfir-Dahav, Dov Monderer, and Moshe Tennenholtz. Bundling Equilibrium in Combinatorial Auctions. Working paper Technion http://ie.technion.ac.il/dov/rndm6.pdf, 2001.
14. Jeffrey S. Rosenschein and Gilad Zlotkin. Rules of Encounter. MIT Press, 1994.
15. S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 1995.
16. L.J. Savage. The Foundations of Statistics. John Wiley and Sons, New York, 1954. Revised and enlarged edition, Dover, New York, 1972.
17. L.S. Shapley. Stochastic Games. In Proc. Nat. Acad. Scie. USA, volume 39, pages 1095-1100, 1953.
18. R. S. Sutton and A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.
19. M. Tennenholtz. Electronic commerce: From game-theoretic and economic models to working protocols. In IJCAI-99, 1999