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Skip to Search Results- 2Regret minimization
- 1Artificial Intelligence
- 1Computer Games
- 1Extensive games
- 1Game theory
- 1Machine Learning
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2012
Bowling, Michael, Zinkevich, Martin
Online learning aims to perform nearly as well as the best hypothesis in hindsight. For some hypothesis classes, though, even finding the best hypothesis offline is challenging. In such offline cases, local search techniques are often employed and only local optimality guaranteed. For online...
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2007
Bowling, Michael, Johanson, Michael, Zinkevich, Martin, Piccione, Carmelo
Technical report TR07-14. Extensive games are a powerful model of multiagent decision-making scenarios with incomplete information. Finding a Nash equilibrium for very large instances of these games has received a great deal of recent attention. In this paper, we describe a new technique for...