Abstract Modular Systems and Solvers
This work addresses the challenge of integrating diverse formalisms for knowledge representation, offering a general framework for solver design, but it appears incremental as it builds on existing transition system approaches from the SAT community.
The paper tackles the problem of designing and analyzing solvers for integrated heterogeneous multi-logic systems by introducing abstract modules and abstract modular systems, showing how these concepts lead to transition systems that represent solvers, with applications demonstrated in answer set programming and propositional logic.
Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience and computational benefits. We introduce concepts of abstract modules and abstract modular systems to study general principles behind the design and analysis of model-finding programs, or solvers, for integrated heterogeneous multi-logic systems. We show how abstract modules and abstract modular systems give rise to transition systems, which are a natural and convenient representation of solvers pioneered by the SAT community. We illustrate our approach by showing how it applies to answer set programming and propositional logic, and to multi-logic systems based on these two formalisms.