32 search results - page 5 / 7 » Learning Policies for Partially Observable Environments: Sca... |
ICASSP
2008
IEEE
15 years 3 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
15 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...
ATAL
2010
Springer
14 years 10 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
15 years 4 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
14 years 9 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...