Synthesizing Filtering Algorithms for Global Chance-Constraints

  title={Synthesizing Filtering Algorithms for Global Chance-Constraints},
  author={Brahim Hnich and Roberto Rossi and Armagan Tarim and Steven David Prestwich},
Stochastic Constraint Satisfaction Problems (SCSPs) are a powerful modeling framework for problems under uncertainty. To solve them is a P-Space task. The only solution approach to date compiles down SCSPs into classical CSPs. This allows the reuse of classical constraint solvers to solve SCSPs, but at the cost of increased space requirements and weak constraint propagation. This paper tries to overcome some of these drawbacks by automatically synthesizing filtering algorithms for global chance… CONTINUE READING

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