10 search results - page 1 / 2 » Planning with Noisy Probabilistic Relational Rules |
JAIR
2010
13 years 3 months ago
2010
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
ICMLA
2009
13 years 2 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
KR
2004
Springer
13 years 10 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
NIPS
2003
13 years 5 months ago
2003
A mobile robot acting in the world is faced with a large amount of sensory data and uncertainty in its action outcomes. Indeed, almost all interesting sequential decision-making d...