On complexity as bounded rationality (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Journal of the ACM (JACM)
Approximation algorithms
Journal of the ACM (JACM)
The complexity of pure Nash equilibria
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Computing correlated equilibria in multi-player games
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Graphical models for game theory
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
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The theories of algorithms and games were arguably born within a year of each other, in the wake of two quite distinct breakthroughs by John von Neumann, in the former case to investigate the great opportunities – as well as the ever mysterious obstacles – in attacking problems by computers, in the latter to model and study rational selfish behavior in the context of interaction, competition and cooperation. For more than half a century the two fields advanced as gloriously as they did separately. There was, of course, a tradition of computational considerations in equilibria initiated by Scarf [13], work on computing Nash and other equilibria [6,7], and reciprocal isolated works by algorithms researchers [8], as well as two important points of contact between the two fields à propos the issues of repeated games and bounded rationality [15] and learning in games [2]. But the current intensive interaction and cross-fertilization between the two disciplines, and the creation of a solid and growing body of work at their interface, must be seen as a direct consequence of the Internet.