Artificial Conflict Sampling for Real Satisfiability Problems

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)(2022)

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摘要
We outline some preliminary ideas on a guided theory assignment of variables in a real (QF_NRA) satisfiability problem. One objective of this approach is to mix the topdown approach of cylindric algebraic decomposition and the bottom-up approach of partial theory assignments of modern SAT/SMT solvers. We use equational constraints and a single strict inequality at a time to artificially create conflicting variable assignment traces, which can later be used in conflict resolution to enrich the constraints of the original satisfiability problem.
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关键词
Conflicting Points,Equational Constraints,Strict Inequalities,Root Isolation
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