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» Reinforcement Learning: An Introduction
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IROS
2006
IEEE
187views Robotics» more  IROS 2006»
14 years 2 months ago
Fast and Stable Learning of Quasi-Passive Dynamic Walking by an Unstable Biped Robot based on Off-Policy Natural Actor-Critic
— Recently, many researchers on humanoid robotics are interested in Quasi-Passive-Dynamic Walking (Quasi-PDW) which is similar to human walking. It is desirable that control para...
Tsuyoshi Ueno, Yutaka Nakamura, Takashi Takuma, To...
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
14 years 25 days ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
NIPS
2008
13 years 9 months ago
Hebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
IROS
2008
IEEE
165views Robotics» more  IROS 2008»
14 years 2 months ago
Mutual development of behavior acquisition and recognition based on value system
Abstract. Both self-learning architecture (embedded structure) and explicit/implicit teaching from other agents (environmental design issue) are necessary not only for one behavior...
Yasutake Takahashi, Yoshihiro Tamura, Minoru Asada
ISDA
2010
IEEE
13 years 6 months ago
Intelligent online case-based planning agent model for real-time strategy games
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industr...
Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrah...