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» Using Machine Learning to Focus Iterative Optimization
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IJCAI
2001
15 years 4 months ago
Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
Gregory Z. Grudic, Lyle H. Ungar
127
Voted
ICML
2000
IEEE
16 years 4 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
WISE
2002
Springer
15 years 8 months ago
An MDP-based Peer-to-Peer Search Server Network
A distributed search system consists of a large number of autonomous search servers logically connected in a peerto-peer network. Each search server maintains a local index of a c...
Yipeng Shen, Dik Lun Lee
IJIT
2004
15 years 4 months ago
Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
ECAI
2004
Springer
15 years 8 months ago
Learning Techniques for Automatic Algorithm Portfolio Selection
The purpose of this paper is to show that a well known machine learning technique based on Decision Trees can be effectively used to select the best approach (in terms of efficien...
Alessio Guerri, Michela Milano