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233views
13 years 11 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
NIPS
2008
15 years 2 months ago
Regularized Policy Iteration
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
NIPS
2003
15 years 2 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»
13 years 8 months 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
ROBOCUP
2004
Springer
114views Robotics» more  ROBOCUP 2004»
15 years 6 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