Answer Set Programming Modulo Theories and Reasoning about Continuous Changes
–arXiv.org Artificial Intelligence
Answer Set Programming Modulo Theories (ASPMT) is a new framework of tight integration of answer set programming (ASP) and satisfiability modulo theories (SMT). Similar to the relationship between first-order logic and SMT, it is based on a recent proposal of the functional stable model semantics by fixing interpretations of background theories. Analogously to a known relationship between ASP and SA T, "tight" ASPMT programs can be translated into SMT instances. We demonstrate the usefulness of ASPMT by enhancing action language C + to handle continuous changes as well as discrete changes. We reformulate the semantics of C + in terms of ASPMT, and show that SMT solvers can be used to compute the language. We also show how the language can represent cumulative effects on continuous resources.
arXiv.org Artificial Intelligence
Jul-8-2025
- Country:
- Asia > South Korea (0.04)
- North America > United States
- Arizona (0.04)
- Genre:
- Research Report (0.64)
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