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» Opposition-Based Reinforcement Learning
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ICMLA
2009
15 years 14 days ago
Multiagent Transfer Learning via Assignment-Based Decomposition
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
Scott Proper, Prasad Tadepalli
140
Voted
AIIDE
2006
15 years 4 months ago
Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games
This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which syn...
Charles A. G. Madeira, Vincent Corruble, Geber Ram...
118
Voted
FLAIRS
2008
15 years 5 months ago
Reinforcement of Local Pattern Cases for Playing Tetris
In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...
Houcine Romdhane, Luc Lamontagne
110
Voted
ML
2002
ACM
100views Machine Learning» more  ML 2002»
15 years 2 months ago
Structure in the Space of Value Functions
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
David J. Foster, Peter Dayan
143
Voted
ICML
2010
IEEE
15 years 21 days ago
Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
Carlton Downey, Scott Sanner