Abstract
In this paper, we study an abductive framework for disjunctive logic programming that provides a new way to understand negation in disjunctive logic programming. We show that the defined framework captures the existing minimal model semantics based on (Extended) Generalised Closed World Assumption ((E)GGWA), This relationship between abduction and minimal model reasoning provides a methodology to develop algorithms for minimal model reasoning. To demonstrate this, we show how a theorem prover, based on restart model elimination calculus, can be modified for abductive reasoning and thus for minimal model reasoning.
This research is a part of project on disjunctive logic programming, undertaken by the AI research group at the Universität Koblenz-Landau, and funded by DFG.
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Aravindan, C. (1996). An abductive framework for negation in disjunctive logic programming. In: Alferes, J.J., Pereira, L.M., Orlowska, E. (eds) Logics in Artificial Intelligence. JELIA 1996. Lecture Notes in Computer Science, vol 1126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61630-6_18
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DOI: https://doi.org/10.1007/3-540-61630-6_18
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