Filters








4 Hits in 1.7 sec

APPSSAT: Approximate probabilistic planning using stochastic satisfiability

Stephen M. Majercik
2007 International Journal of Approximate Reasoning  
We describe APPSSAT, an anytime probabilistic contingent planner based on ZANDER, a probabilistic contingent planner that operates by converting the planning problem to a stochastic satisfiability (Ssat  ...  ) and attempts to construct an approximation of the optimal plan that succeeds under those circumstances, improving that plan as time permits.  ...  In Section 3, we describe how ZANDER uses stochastic satisfiability to solve probabilistic planning problems.  ... 
doi:10.1016/j.ijar.2006.06.016 fatcat:b57cpx7jvbg6pgaipe7qdesfni

APPSSAT: Approximate Probabilistic Planning Using Stochastic Satisfiability [chapter]

Stephen M. Majercik
2005 Lecture Notes in Computer Science  
We describe APPSSAT, an anytime probabilistic contingent planner based on ZANDER, a probabilistic contingent planner that operates by converting the planning problem to a stochastic satisfiability (Ssat  ...  ) and attempts to construct an approximation of the optimal plan that succeeds under those circumstances, improving that plan as time permits.  ...  In Section 3, we describe how ZANDER uses stochastic satisfiability to solve probabilistic planning problems.  ... 
doi:10.1007/11518655_19 fatcat:zej4ze2yzvajhj5burprwjjqpa

Deliberation scheduling using GSMDPs in stochastic asynchronous domains

Kurt D. Krebsbach
2009 International Journal of Approximate Reasoning  
) occur asynchronously and stochastically.  ...  In particular, we use GSMDPs to more accurately model domains in which planning and execution occur concurrently, plan improvement actions have uncertain effects and duration, and events (such as threats  ...  Thanks also to Vu Ha and David Musliner for fruitful discussions and useful comments on earlier drafts, and to anonymous IJAR reviewers who provided many thoughtful and specific suggestions for the improvement  ... 
doi:10.1016/j.ijar.2009.04.007 fatcat:japw4bafgbajton7srkabds5pm

Hybrid metaheuristics for stochastic constraint programming

S. D. Prestwich, S. A. Tarim, R. Rossi, B. Hnich
2014 Constraints  
Secondly we show how to use standard filtering algorithms to handle hard constraints more efficiently during search.  ...  Stochastic Constraint Programming (SCP) is an extension of Constraint Programming for modelling and solving combinatorial problems involving uncertainty.  ...  Use binary stochastic variables b i (i = 1 . . .  ... 
doi:10.1007/s10601-014-9170-x fatcat:cqv5c44wojgq5nwkzrt2g7ebu4