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ICML
2010
IEEE
15 years 3 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
ESANN
2006
15 years 3 months ago
A multiagent architecture for concurrent reinforcement learning
In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions ...
Victor Uc Cetina
ICCBR
2007
Springer
15 years 8 months ago
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
Thomas Gabel, Martin Riedmiller
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
144
Voted
JAIR
2002
163views more  JAIR 2002»
15 years 2 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu