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ICML
1998
IEEE
14 years 8 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
IJCAI
1989
13 years 8 months ago
Selective Learning of Macro-operators with Perfect Causality
A macro-operator is an integrated operator consisting of plural primitive operators and enables a problem solver to solve more efficiently. However, if a learning system generates...
Seiji Yamada, Sabinro Tsuji
ABIALS
2008
Springer
13 years 9 months ago
Anticipatory Learning Classifier Systems and Factored Reinforcement Learning
Factored Reinforcement Learning (frl) is a new technique to solve Factored Markov Decision Problems (fmdps) when the structure of the problem is not known in advance. Like Anticipa...
Olivier Sigaud, Martin V. Butz, Olga Kozlova, Chri...
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
14 years 2 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
SIGGRAPH
2010
ACM
14 years 4 days ago
Optimal feedback control for character animation using an abstract model
Feedback Control for Character Animation Using an Abstract Model Yuting Ye C. Karen Liu Georgia Institute of Technology∗ Real-time adaptation of a motion capture sequence to vir...
Yuting Ye, C. Karen Liu