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EUROCOLT
1997
Springer
15 years 8 months ago
Control Structures in Hypothesis Spaces: The Influence on Learning
In any learnability setting, hypotheses are conjectured from some hypothesis space. Studied herein are the influence on learnability of the presence or absence of certain control ...
John Case, Sanjay Jain, Mandayam Suraj
AAMAS
2007
Springer
15 years 4 months ago
Parallel Reinforcement Learning with Linear Function Approximation
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Matthew Grounds, Daniel Kudenko
ICML
2001
IEEE
16 years 5 months ago
Round Robin Rule Learning
In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is kno...
Johannes Fürnkranz
AUSAI
2003
Springer
15 years 9 months ago
Learning Action Selection Network of Intelligent Agent
Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavi...
Eun-Kyung Yun, Sung-Bae Cho
ICML
2000
IEEE
15 years 8 months ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens