Abstract | ||
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A fact apparently not observed earlier in the literature of nonmonotonic reasoning is that Reiter, in his default logic paper, did not directly formalize informal defaults. Instead, he translated a default into a certain natural language proposition and provided a formalization of the latter. A few years later, Moore noted that propositions like the one used by Reiter are fundamentally different than defaults and exhibit a certain autoepistemic nature. Thus, Reiter had developed his default logic as a formalization of autoepistemic propositions rather than of defaults. The first goal of this paper is to show that some problems of Reiter's default logic as a formal way to reason about informal defaults are directly attributable to the autoepistemic nature of default logic and to the mismatch between informal defaults and the Reiter's formal defaults, the latter being a formal expression of the autoepistemic propositions Reiter used as a representation of informal defaults. The second goal of our paper is to compare the work of Reiter and Moore. While each of them attempted to formalize autoepistemic propositions, the modes of reasoning in their respective logics were different. We revisit Moore's and Reiter's intuitions and present them from the perspective of autotheoremhood, where theories can include propositions referring to the theory's own theorems. We then discuss the formalization of this perspective in the logics of Moore and Reiter, respectively, using the unifying semantic framework for default and autoepistemic logics that we developed earlier. We argue that Reiter's default logic is a better formalization of Moore's intuitions about autoepistemic propositions than Moore's own autoepistemic logic. |
Year | Venue | Keywords |
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2011 | CoRR | nonmonotonic reasoning,default logic,artificial intelligent,natural language |
Field | DocType | Volume |
Default logic,Semantic framework,Mathematical economics,Proposition,Autoepistemic logic,Computer science,Intuition,Default,Non-monotonic logic,Artificial intelligence,Machine learning | Journal | abs/1108.3278 |
Citations | PageRank | References |
5 | 0.40 | 20 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Marc Denecker | 1 | 1626 | 106.40 |
Victor W. Marek | 2 | 788 | 49.47 |
Miroslaw Truszczynski | 3 | 1494 | 162.36 |