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JIRS
2000
144views more  JIRS 2000»
15 years 3 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
ROBOCUP
2004
Springer
114views Robotics» more  ROBOCUP 2004»
15 years 9 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 5 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
122
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ML
2002
ACM
133views Machine Learning» more  ML 2002»
15 years 3 months ago
Finite-time Analysis of the Multiarmed Bandit Problem
Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while t...
Peter Auer, Nicolò Cesa-Bianchi, Paul Fisch...
COLT
2010
Springer
15 years 2 months ago
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
Junya Honda, Akimichi Takemura