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GECCO
2009
Springer
15 years 10 months ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...
ICALT
2006
IEEE
15 years 10 months ago
Auto-Adaptive Questions in E-Learning System
All books entitled “Learn … with 1000 exercises” have in common the same basic principle. They aim to supply enough material to students so that they may better understand t...
Enrique Lazcorreta, Federico Botella, Antonio Fern...
ICML
1994
IEEE
15 years 7 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager
ATAL
2008
Springer
15 years 6 months ago
Approximate predictive state representations
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
NIPS
2001
15 years 5 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr