447 search results - page 24 / 90 » Explaining inferences in Bayesian networks |
IROS
2007
IEEE
14 years 1 months ago
2007
IEEE
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
ICML
2009
IEEE
14 years 8 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...
SUM
2009
Springer
14 years 2 months ago
2009
Springer
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
CDC
2009
IEEE
14 years 9 days ago
2009
IEEE
— Bayesian networks have extensively been used in numerous fields including artificial intelligence, decision theory and control. Its ability to utilize noisy and missing data ...
UAI
2004
13 years 9 months ago
2004
We characterize probabilities in Bayesian networks in terms of algebraic expressions called quasi-probabilities. These are arrived at by casting Bayesian networks as noisy AND-OR-...