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» MDPs: Learning in Varying Environments
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JMLR
2002
79views more  JMLR 2002»
13 years 4 months ago
MDPs: Learning in Varying Environments
Istvan Szita, Bálint Takács, Andr&aa...
AAAI
2011
12 years 4 months ago
Learned Behaviors of Multiple Autonomous Agents in Smart Grid Markets
One proposed approach to managing a large complex Smart Grid is through Broker Agents who buy electrical power from distributed producers, and also sell power to consumers, via a ...
Prashant P. Reddy, Manuela M. Veloso
ICML
2007
IEEE
14 years 5 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ML
2002
ACM
100views Machine Learning» more  ML 2002»
13 years 4 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
ICML
2008
IEEE
14 years 5 months ago
An object-oriented representation for efficient reinforcement learning
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
Carlos Diuk, Andre Cohen, Michael L. Littman