Prime Implicates and Prime Implicants: From Propositional to Modal Logic
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Abstract (arXiv)
Prime implicates and prime implicants have proven relevant to a number of areas of artificial intelligence, most notably abductive reasoning and knowledge compilation. The purpose of this paper is to examine how these notions might be appropriately extended from propositional logic to the modal logic K. We begin the paper by considering a number of potential definitions of clauses and terms for K. The different definitions are evaluated with respect to a set of syntactic, semantic, and complexity-theoretic properties characteristic of the propositional definition. We then compare the definitions with respect to the properties of the notions of prime implicates and prime implicants that they induce. While there is no definition that perfectly generalizes the propositional notions, we show that there does exist one definition which satisfies many of the desirable properties of the propositional case. In the second half of the paper, we consider the computational properties of the selected definition. To this end, we provide sound and complete algorithms for generating and recognizing prime implicates, and we show the prime implicate recognition task to be PSPACE-complete. We also prove upper and lower bounds on the size and number of prime implicates. While the paper focuses on the logic K, all of our results hold equally well for multi-modal K and for concept expressions in the description logic ALC.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jan 2014.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1.
4 papers.
- 2022Logic-Based Explainability in Machine Learningcited by 47
- 2022On Tackling Explanation Redundancy in Decision Treescited by 44
- 2021Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Beliefcited by 7
- 2024Abductive Reasoning in a Paraconsistent Frameworkcited by 2
- 2024Abductive Reasoning in a Paraconsistent Framework1 Aug 2024
- 2022Logic-Based Explainability in Machine Learning24 Oct 2022
- 2022On Tackling Explanation Redundancy in Decision Trees20 May 2022
- 2021Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief6 Oct 2021