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EWLR
1997
Springer
13 years 11 months ago
Learning Complex Robot Behaviours by Evolutionary Computing with Task Decomposition
Building robots can be a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to cope the...
Wei-Po Lee, John Hallam, Henrik Hautop Lund
TFS
2008
94views more  TFS 2008»
13 years 6 months ago
Hierarchical Fuzzy CMAC for Nonlinear Systems Modeling
Abstract--Since the fuzzy cerebellar model articulation controller (FCMAC) uses linguistic variables, it is highly intuitive and easily comprehended. Despite the FCMAC's good ...
Wen Yu, Floriberto Ortiz Rodriguez, Marco A. Moren...
ATAL
2006
Springer
13 years 11 months ago
Learning to identify winning coalitions in the PAC model
We consider PAC learning of simple cooperative games, in which the coalitions are partitioned into "winning" and "losing" coalitions. We analyze the complexity...
Ariel D. Procaccia, Jeffrey S. Rosenschein
ICML
2006
IEEE
14 years 8 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh
ICML
2007
IEEE
14 years 8 months ago
Reinforcement learning by reward-weighted regression for operational space control
Many robot control problems of practical importance, including operational space control, can be reformulated as immediate reward reinforcement learning problems. However, few of ...
Jan Peters, Stefan Schaal