A first-order conditional logic for prototypical properties
Artificial Intelligence
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Propositional knowledge base revision and minimal change
Artificial Intelligence
What does a conditional knowledge base entail?
Artificial Intelligence
Nonmonotonic inference based on expectations
Artificial Intelligence
Conditional logics of normality: a modal approach
Artificial Intelligence
ALC + T: a Preferential Extension of Description Logics
Fundamenta Informaticae - Advances in Computational Logic (CIL C08)
Preferential Reasoning for Modal Logics
Electronic Notes in Theoretical Computer Science (ENTCS)
Semantic foundation for preferential description logics
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Normal modal preferential consequence
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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We introduce Propositional Typicality Logic (PTL), a logic for reasoning about typicality. We do so by enriching classical propositional logic with a typicality operator of which the intuition is to capture the most typical (or normal) situations in which a formula holds. The semantics is in terms of ranked models as studied in KLM-style preferential reasoning. This allows us to show that rational consequence relations can be embedded in our logic. Moreover we show that we can define consequence relations on the language of PTL itself, thereby moving beyond the propositional setting. Building on the existing link between propositional rational consequence and belief revision, we show that the same correspondence holds for rational consequence and belief revision on PTL. We investigate entailment for PTL, and propose two appropriate notions thereof.