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ICML
1998
IEEE
16 years 19 days 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
ICALT
2008
IEEE
15 years 6 months ago
Multisensory Games for Dyslexic Children
A significant problem faced by dyslexic children is a lack of learning technologies designed to help children learn in settings when there is no personal teaching assistance. This...
James Ohene-Djan, Rahima Begum
ICRA
2010
IEEE
128views Robotics» more  ICRA 2010»
14 years 10 months ago
A game-theoretic procedure for learning hierarchically structured strategies
— This paper addresses the problem of acquiring a hierarchically structured robotic skill in a nonstationary environment. This is achieved through a combination of learning primi...
Benjamin Rosman, Subramanian Ramamoorthy
SAGT
2009
Springer
192views Game Theory» more  SAGT 2009»
15 years 6 months ago
Learning and Approximating the Optimal Strategy to Commit To
Computing optimal Stackelberg strategies in general two-player Bayesian games (not to be confused with Stackelberg strategies in routing games) is a topic that has recently been ga...
Joshua Letchford, Vincent Conitzer, Kamesh Munagal...
UAI
2000
15 years 1 months ago
Learning to Cooperate via Policy Search
Cooperative games are those in which both agents share the same payoff structure. Valuebased reinforcement-learning algorithms, such as variants of Q-learning, have been applied t...
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Les...