Max-SAT-based synthesis of optimal and Nash equilibrium strategies for multi-agent systems

Timm, Nils; Botha, Josua; Jordaan, Steven

doi:10.1016/j.scico.2023.102946

Cited by 2 publications

(1 citation statement)

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“…Real-world problems encoded into SAT are composed of various constraints, among which the At-Most-K constraints often become the bottleneck of computational complexity [2]. Regarding state-of-the-art SAT papers, Timm et al used SAT for the verification of multi-agent systems [5]. In this situation, an efficient encoding method is needed, especially for At-Most-K constraints for large K. To date, various encoding methods for At-Most-K constraints have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Fractional Encoding of At-Most-K Constraints on SAT

Yonekura,

Nishimura

2023

Electronics

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The satisfiability problem (SAT) in propositional logic determines if there is an assignment of values that makes a given propositional formula true. Recently, fast SAT solvers have been developed, and SAT encoding research has gained attention. This enables various real-world problems to be transformed into SAT and solved, realizing a solution to the original problems. We propose a new encoding method, Fractional Encoding, which focuses on the At-Most-K constraints—a bottleneck of computational complexity—and reduces the scale of logical expressions by dividing target variables. Furthermore, we confirm that Fractional Encoding outperforms existing methods in terms of the number of generated clauses and required auxiliary variables. Hence, it enables the efficient solving of real-world problems like planning and hardware verification.

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Section: Introductionmentioning

confidence: 99%