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» Variational methods for Reinforcement Learning
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ECML
2003
Springer
14 years 25 days ago
A New Way to Introduce Knowledge into Reinforcement Learning
We present in this paper a method to introduce a priori knowledge into reinforcement learning using temporally extended actions. The aim of our work is to reduce the learning time ...
Pascal Garcia
SAC
2005
ACM
14 years 1 months ago
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process
This paper presents a novel model of reinforcement learning agents. A feature of our learning agent model is to integrate analytic hierarchy process (AHP) into a standard reinforc...
Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narih...
ICML
1998
IEEE
14 years 8 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
IAT
2003
IEEE
14 years 27 days ago
Asymmetric Multiagent Reinforcement Learning
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
Ville Könönen