44 search results - page 2 / 9 » Approximate inference for planning in stochastic relational ... |
AIPS
2008
13 years 7 months ago
2008
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
AAAI
1997
13 years 6 months ago
1997
We report on the performance of an enhanced version of the “Davis-Putnam” (DP) proof procedure for propositional satisfiability (SAT) on large instances derived from realworld...
AIPS
2007
13 years 7 months ago
2007
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
AIPS
2008
13 years 7 months ago
2008
Dynamic programming algorithms have been successfully applied to propositional stochastic planning problems by using compact representations, in particular algebraic decision diag...
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...