@InProceedings{nudelman04a,
  author =	 {Eugene Nudelman and Jennifer Wortman and Kevin
                  Leyton-Brown and Yoav Shoham},
  title =	 {Run the {GAMUT}: A Comprehensive Approach to
                  Evaluating Game-Theoretic Algorithms},
  booktitle =	 {Proceedings of the Third International Joint
                  Conference on Autonomous Agents and MultiAgent
                  Systems},
  crossref =	 {aamas04},
  year =	 2004,
  googleid = 	 {6m6uDpBdqyQJ:scholar.google.com/},
  abstract =	 {We present GAMUT, a suite of game generators
                  designed for testing game-theoretic algorithms. We
                  explain why such a generator is necessary, offer a
                  way of visualizing relationships between the sets of
                  games supported by GAMUT, and give an overview of
                  GAMUT's architecture. We highlight the importance of
                  using comprehensive test data by benchmarking
                  existing algorithms. We show surprisingly large
                  variation in algorithm performance across different
                  sets of games for two widely-studied problems:
                  computing Nash equilibria and multiagent learning in
                  repeated games.},
  keywords =     {game-theory multiagent learning},
  url = 	 {http://jmvidal.cse.sc.edu/library/nudelman04a.pdf},
  cluster = 	 {2642308479685914346}
}