The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Computer Science and Game Theory

  • Joseph Y. Halpern
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2133

Abstract

Work at the intersection of computer science and game theory is briefly surveyed, with a focus on the work in computer science. In particular, the following topics are considered: various roles of computational complexity in game theory, including modelling bounded rationality, its role in mechanism design, and the problem of computing Nash equilibria; the price of anarchy, that is, the cost of using decentralizing solution to a problem; and interactions between distributed computing and game theory.

Keywords

Algorithmic knowledge Algorithmic mechanism design Bayesian networks Bounded rationality Byzantine agreement Cheap talk Coalitions Combinatorial auctions Complexity theory Computational complexity Computer science and game theory Distributed computing Efficient representation of games Game theory Gibbard–Satterthwaite th Implementing mediators Interactive epistemology k-resilient equilibrium (k,t)-robust equilibrium Learning Mechanism design Markov networks Nash equilibrium Price of anarchy Prisoner’s Dilemma Regret Strategic voting Tit for tat Voting 
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Notes

Acknowledgment

The work for this article was supported in part by NSF under grants CTC-0208535 and ITR-0325453, by ONR under grant N00014-02-1-0455, by the DoD Multidisciplinary University Research Initiative (MURI) program administered by the ONR under grants N00014-01-1-0795 and N00014-04-1-0725, and by AFOSR under grant F49620-02-1-0101. Thanks to Larry Blume, Christos Papadimitriou, Ilya Segal, Éva Tardos, and Moshe Tennenholtz for useful comments.

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Authors and Affiliations

  • Joseph Y. Halpern
    • 1
  1. 1.