Booth, RMeyer, TVarzinczak, I2012-11-222012-11-222012-09Booth, R, Meyer, T and Varzinczak, I. PTL: A Propositional Typicality Logic. 13th European Conference on Logics in Artificial Intelligence (JELIA), Toulouse, France, 26-28 September 2012. In: Lecture Notes in Computer Science Volume 7519, 2012, pp 107-119978-3-642-33352-1978-3-642-33353-8http://link.springer.com/chapter/10.1007%2F978-3-642-33353-8_9http://hdl.handle.net/10204/6358Copyright: 2012 Springer-Verlag. Lecture Notes in Computer Science Volume 7519, 2012, pp 107-119We 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.enPropositional Typicality LogicPTLArtificial IntelligenceNonmonotonic reasoningBelief revisionRationalitySemanticsConference PresentationBooth, R., Meyer, T., & Varzinczak, I. (2012). PTL: A Propositional Typicality Logic. Springer. http://hdl.handle.net/10204/6358Booth, R, T Meyer, and I Varzinczak. "PTL: A Propositional Typicality Logic." (2012): http://hdl.handle.net/10204/6358Booth R, Meyer T, Varzinczak I, PTL: A Propositional Typicality Logic; Springer; 2012. http://hdl.handle.net/10204/6358 .TY - Conference Presentation AU - Booth, R AU - Meyer, T AU - Varzinczak, I AB - 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. DA - 2012-09 DB - ResearchSpace DP - CSIR KW - Propositional Typicality Logic KW - PTL KW - Artificial Intelligence KW - Nonmonotonic reasoning KW - Belief revision KW - Rationality KW - Semantics LK - https://researchspace.csir.co.za PY - 2012 SM - 978-3-642-33352-1 SM - 978-3-642-33353-8 T1 - PTL: A Propositional Typicality Logic TI - PTL: A Propositional Typicality Logic UR - http://hdl.handle.net/10204/6358 ER -