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» Iterative Learning Control - Monotonicity and Optimization
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ICML
2005
IEEE
15 years 10 months ago
Finite time bounds for sampling based fitted value iteration
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
Csaba Szepesvári, Rémi Munos
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 1 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
ATAL
2008
Springer
14 years 11 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
NIPS
2001
14 years 11 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
PAA
2010
14 years 8 months ago
A simple iterative algorithm for parsimonious binary kernel Fisher discrimination
By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant ana...
Robert F. Harrison, Kitsuchart Pasupa