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» Algorithm Selection using Reinforcement Learning
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AIIDE
2008
15 years 5 months ago
Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...
ML
2008
ACM
152views Machine Learning» more  ML 2008»
15 years 3 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...
146
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AGI
2008
15 years 4 months ago
Transfer Learning and Intelligence: an Argument and Approach
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
Matthew E. Taylor, Gregory Kuhlmann, Peter Stone
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
ATAL
2008
Springer
15 years 5 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...