250 search results - page 4 / 50 » Learning action effects in partially observable domains |
ICRA
2007
IEEE
13 years 11 months ago
2007
IEEE
— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
ICMLA
2008
13 years 6 months ago
2008
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
FORTE
2004
13 years 6 months ago
2004
Abstract. Monitoring large distributed concurrent systems is a challenging task. In this paper we formulate (model-based) diagnosis by means of hidden state history reconstruction,...