Integer and combinatorial optimization
Integer and combinatorial optimization
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Playing large games using simple strategies
Proceedings of the 4th ACM conference on Electronic commerce
Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Exponentially Many Steps for Finding a Nash Equilibrium in a Bimatrix Game
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Simple search methods for finding a Nash equilibrium
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Complexity results about Nash equilibria
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Computing the optimal strategy to commit to
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Finding equilibria in large sequential games of imperfect information
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
A technique for reducing normal-form games to compute a Nash equilibrium
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Perspectives on multiagent learning
Artificial Intelligence
Lossless abstraction of imperfect information games
Journal of the ACM (JACM)
An efficient heuristic approach for security against multiple adversaries
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Approximate Equilibria for Strategic Two Person Games
SAGT '08 Proceedings of the 1st International Symposium on Algorithmic Game Theory
Coordinating randomized policies for increasing security of agent systems
Information Technology and Management
Algorithms for rationalizability and CURB sets
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Efficient algorithms to solve Bayesian Stackelberg games for security applications
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Average-reward decentralized Markov decision processes
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
The price of stability in selfish scheduling games
Web Intelligence and Agent Systems
An optimization approach for approximate Nash equilibria
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Approximation guarantees for fictitious play
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
First-order mixed integer linear programming
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Computing equilibria by incorporating qualitative models?
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Local search techniques for computing equilibria in two-player general-sum strategic-form games
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
An investigation into mathematical programming for finite horizon decentralized POMDPs
Journal of Artificial Intelligence Research
Computing exact and approximate Nash equilibria in 2-player games
AAIM'10 Proceedings of the 6th international conference on Algorithmic aspects in information and management
Algorithms for closed under rational behavior (CURB) sets
Journal of Artificial Intelligence Research
Computing a self-confirming equilibrium in two-player extensive-form games
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Solving Stackelberg games with uncertain observability
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Solving strategic bargaining with arbitrary one-sided uncertainty
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Approximate nash equilibria in bimatrix games
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
New results on the verification of Nash refinements for extensive-form games
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Fuzzy Equilibrium Logic: Declarative Problem Solving in Continuous Domains
ACM Transactions on Computational Logic (TOCL)
Finding a nash equilibrium by asynchronous backtracking
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Using representative strategies for finding nash equilibria
Proceedings of the 15th annual conference on Genetic and evolutionary computation
On the verification and computation of strong nash equilibrium
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Differential evolution as a new method of computing nash equilibria
Transactions on Computational Collective Intelligence IX
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We present, to our knowledge, the first mixed integer program (MIP) formulations for finding Nash equilibria in games (specifically, two-player normal form games). We study different design dimensions of search algorithms that are based on those formulations. Our MIP Nash algorithm outperforms Lemke-Howson but not Porter-Nudelman-Shoham (PNS) on GAMUT data. We argue why experiments should also be conducted on games with equilibria with medium-sized supports only, and present a methodology for generating such games. On such games MIP Nash drastically outperforms PNS but not Lemke-Howson. Certain MIP Nash formulations also yield anytime algorithms for Ε-equilibrium. with provable bounds. Another advantage of MIP Nash is that it can be used to find an optimal equilibrium (according to various objectives). The prior algorithms can be extended to that setting, but they are orders of magnitude slower.