An approximative inference method for solving ∃∀SO satisfiability problems

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Abstract

This paper considers the fragment ∃∀SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (ΣP 2 ) and many of these problems are often solved approximately. In this paper, we develop a general approximative method, i.e., a sound but incomplete method, for solving ∃∀SO satisfiability problems. We use a syntactic representation of a constraint propagation method for firstorder logic to transform such an ∃∀SO satisfiability problem to an 9SO(ID) satisfiability problem (second-order logic, extended with inductive definitions). The finite domain satis fiability problem for the latter language is in NP and can be handled by several existing solvers. Inductive definitions are a powerful knowledge representation tool, and this motivates us to also approximate ∃∀SO(ID) problems. In order to do this, we first show how to perform propagation on such inductive definitions. Next, we use this to approximate ∃∀SO(ID) satisfiability problems. All this provides a general theoretical framework for a number of approximative methods in the literature. Moreover, we also show how we can use this framework for solving practical useful problems, such as conformant planning, in an effective way. © 2012 AI Access Foundation.

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APA

Vlaeminck, H., Vennekens, J., Denecker, M., & Bruynooghe, M. (2012). An approximative inference method for solving ∃∀SO satisfiability problems. Journal of Artificial Intelligence Research, 45, 79–124. https://doi.org/10.1613/jair.3658

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