Combining local search techniques and path following for bimatrix games

Computing a Nash equilibrium (NE) is a central task in computer science. An NE is a particularly appropriate solution concept for two-agent settings because coalitional deviations are not an issue. However, even in this case, finding an NE is PPAD-complete. In this paper, we combine path following algorithms with local search techniques to design new algorithms for finding exact and approximate NEs. We show that our algorithms largely outperform the state of the art and that almost all the known benchmark game classes are easily solvable or approximable (except for the GAMUT CovariantGame-Rand class).

[1]  Emile H. L. Aarts,et al.  Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series) , 2007 .

[2]  Pierfrancesco La Mura Game Networks , 2000, UAI.

[3]  Nicola Gatti,et al.  Local search techniques for computing equilibria in two-player general-sum strategic-form games , 2010, AAMAS.

[4]  B. Stengel Algorithmic Game Theory: Equilibrium Computation for Two-Player Games in Strategic and Extensive Form , 2007 .

[5]  Shang-Hua Teng Smoothed Analysis of Algorithms and Heuristics , 2005, COCOON.

[6]  Pierfrancesco La Mura,et al.  SIMULATED ANNEALING OF GAME EQUILIBRIA : A SIMPLE ADAPTIVE PROCEDURE LEADING TO NASHEQUILIBRIUMBY , 2001 .

[7]  Shang-Hua Teng,et al.  Foundations of Computational Mathematics, Santander 2005: Smoothed Analysis of Algorithms and Heuristics , 2006 .

[8]  Paul G. Spirakis,et al.  An Optimization Approach for Approximate Nash Equilibria , 2007, WINE.

[9]  Xi Chen,et al.  Computing Nash Equilibria: Approximation and Smoothed Complexity , 2006, 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06).

[10]  Nicola Gatti,et al.  Local Search Methods for Finding a Nash Equilibrium in Two-Player Games , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[11]  Bruno Codenotti,et al.  An experimental analysis of Lemke-Howson algorithm , 2008, ArXiv.

[12]  H. Kuk On equilibrium points in bimatrix games , 1996 .

[13]  Rahul Savani,et al.  Hard‐to‐Solve Bimatrix Games , 2006 .

[14]  Bernhard von Stengel,et al.  Computing Normal Form Perfect Equilibria for Extensive Two-Person Games , 2002 .

[15]  Evangelos Markakis,et al.  New algorithms for approximate Nash equilibria in bimatrix games , 2010, Theor. Comput. Sci..

[16]  Panagiota N. Panagopoulou,et al.  Polynomial algorithms for approximating Nash equilibria of bimatrix games , 2006, Theor. Comput. Sci..

[17]  D. Avis,et al.  Enumeration of Nash equilibria for two-player games , 2010 .

[18]  Michela Milano,et al.  Constraint and Integer Programming , 2004, Operations Research/Computer Science Interfaces Series.

[19]  Yoav Shoham,et al.  Run the GAMUT: a comprehensive approach to evaluating game-theoretic algorithms , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[20]  Michela Milano,et al.  Constraint and Integer Programming: Toward a Unified Methodology (Operations Research/Computer Science Interfaces, 27) , 2003 .

[21]  Yoav Shoham,et al.  Simple search methods for finding a Nash equilibrium , 2004, Games Econ. Behav..

[22]  Emile H. L. Aarts,et al.  Theoretical aspects of local search , 2006, Monographs in Theoretical Computer Science. An EATCS Series.

[23]  Xiaotie Deng,et al.  Settling the complexity of computing two-player Nash equilibria , 2007, JACM.

[24]  Vincent Conitzer,et al.  Mixed-Integer Programming Methods for Finding Nash Equilibria , 2005, AAAI.

[25]  M. Dufwenberg Game theory. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[26]  Paul W. Goldberg,et al.  The complexity of computing a Nash equilibrium , 2006, STOC '06.