Computing pure Bayesian-Nash equilibria in games with finite actions and continuous types

• Published in: Artificial intelligence 2013-02, Vol.195, p.106-139
• Main Authors: Rabinovich, Zinovi, Naroditskiy, Victor, Gerding, Enrico H., Jennings, Nicholas R.
• Format: Article
• Language: English
• Subjects: Algorithmic game theory; Applied sciences; Artificial intelligence; Bayes–Nash equilibrium; Computer science; control theory; systems; Decision theory. Utility theory; Epsilon-Nash equilibrium; Exact sciences and technology; Fictitious play; Game theory; Learning and adaptive systems; Operational research and scientific management; Operational research. Management science; Portfolio theory; Simultaneous auctions
• ISSN: 0004-3702; 1872-7921
• DOI: 10.1016/j.artint.2012.09.007

We extend the well-known fictitious play (FP) algorithm to compute pure-strategy Bayesian-Nash equilibria in private-value games of incomplete information with finite actions and continuous types (G-FACTs). We prove that, if the frequency distribution of actions (fictitious play beliefs) converges, then there exists a pure-strategy equilibrium strategy that is consistent with it. We furthermore develop an algorithm to convert the converged distribution of actions into an equilibrium strategy for a wide class of games where utility functions are linear in type. This algorithm can also be used to compute pure ϵ-Nash equilibria when distributions are not fully converged. We then apply our algorithm to find equilibria in an important and previously unsolved game: simultaneous sealed-bid, second-price auctions where various types of items (e.g., substitutes or complements) are sold. Finally, we provide an analytical characterisation of equilibria in games with linear utilities. Specifically, we show how equilibria can be found by solving a system of polynomial equations. For a special case of simultaneous auctions, we also solve the equations confirming the results obtained numerically.