32 search results - page 5 / 7 » Learning Policies for Partially Observable Environments: Sca... |
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
ICML
2004
IEEE
14 years 8 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...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
IJRR
2008
13 years 7 months ago
2008
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...