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189
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GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
214
Voted
ICML
2007
IEEE
16 years 8 months ago
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Chee Wee Phua, Robert Fitch
185
Voted
ICML
2009
IEEE
16 years 8 months ago
Kernelized value function approximation for reinforcement learning
Gavin Taylor, Ronald Parr
ICML
2008
IEEE
16 years 8 months ago
An analysis of reinforcement learning with function approximation
Francisco S. Melo, Sean P. Meyn, M. Isabel Ribeiro
184
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NIPS
2001
15 years 8 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar