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ICML
2003
IEEE
14 years 8 months ago
BL-WoLF: A Framework For Loss-Bounded Learnability In Zero-Sum Games
We present BL-WoLF, a framework for learnability in repeated zero-sum games where the cost of learning is measured by the losses the learning agent accrues (rather than the number...
Vincent Conitzer, Tuomas Sandholm
MFCS
2009
Springer
14 years 2 months ago
Stochastic Games with Finitary Objectives
Abstract. The synthesis of a reactive system with respect to an ωregular specification requires the solution of a graph game. Such games have been extended in two natural ways. F...
Krishnendu Chatterjee, Thomas A. Henzinger, Floria...
APAL
2010
111views more  APAL 2010»
13 years 7 months ago
Resource modalities in tensor logic
The description of resources in game semantics has never achieved the simplicity and precision of linear logic, because of the misleading conception that linear logic is more prim...
Paul-André Melliès, Nicolas Tabareau
ICML
2008
IEEE
14 years 8 months ago
Strategy evaluation in extensive games with importance sampling
Typically agent evaluation is done through Monte Carlo estimation. However, stochastic agent decisions and stochastic outcomes can make this approach inefficient, requiring many s...
Michael H. Bowling, Michael Johanson, Neil Burch, ...
ICML
1998
IEEE
14 years 8 months ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman