9 search results - page 1 / 2 » APPSSAT: Approximate Probabilistic Planning Using Stochastic... |
ECSQARU
2005
Springer
13 years 10 months ago
2005
Springer
JAIR
2010
13 years 3 months ago
2010
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
TROB
2010
13 years 3 months ago
2010
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
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...
JAIR
2008
13 years 4 months ago
2008
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...