301 search results - page 36 / 61 » Learning to Select a Good Translation |
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
NIPS
2003
13 years 11 months ago
2003
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
AAAI
1998
13 years 11 months ago
1998
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedures for accurately labeling future unlabeled sequences. The choice of representat...
EUROCAST
2007
Springer
14 years 3 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
IWANN
1999
Springer
14 years 1 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...