Computer Science – Artificial Intelligence
Scientific paper
2009-03-06
ECAI 2002: 111-115
Computer Science
Artificial Intelligence
Proceedings of the 15th Eureopean Conference on Artificial Intelligence
Scientific paper
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability. We give a semantics for stochastic constraint programs, and propose a number of complete algorithms and approximation procedures. Finally, we discuss a number of extensions of stochastic constraint programming to relax various assumptions like the independence between stochastic variables, and compare with other approaches for decision making under uncertainty.
No associations
LandOfFree
Stochastic Constraint Programming does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Stochastic Constraint Programming, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Stochastic Constraint Programming will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-135675