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Using SMT Solvers to Validate Models for AI Problems
[article]
2019
arXiv
pre-print
Artificial Intelligence problems, ranging form planning/scheduling up to game control, include an essential crucial step: describing a model which accurately defines the problem's required data, requirements, allowed transitions and established goals. The ways in which a model can fail are numerous and often lead to a failure of search strategies to provide a quick, optimal, or even any solution. This paper proposes using SMT (Satisfiability Modulo Theories) solvers, such as Z3, to check the
arXiv:1903.09475v1
fatcat:uxqx5kvpczdprmbojwjnidssee