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NIPS
2003
15 years 6 months ago
Approximate Planning in POMDPs with Macro-Actions
Recent research has demonstrated that useful POMDP solutions do not require consideration of the entire belief space. We extend this idea with the notion of temporal abstraction. ...
Georgios Theocharous, Leslie Pack Kaelbling
CORR
2012
Springer
216views Education» more  CORR 2012»
14 years 14 days ago
Fractional Moments on Bandit Problems
Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit proble...
Ananda Narayanan B., Balaraman Ravindran
174
Voted
ROBOCUP
2004
Springer
114views Robotics» more  ROBOCUP 2004»
15 years 10 months ago
Modular Learning System and Scheduling for Behavior Acquisition in Multi-agent Environment
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
Yasutake Takahashi, Kazuhiro Edazawa, Minoru Asada
IJCAI
2007
15 years 6 months ago
Effective Control Knowledge Transfer through Learning Skill and Representation Hierarchies
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
Mehran Asadi, Manfred Huber
ECML
2006
Springer
15 years 8 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....