Bridging the gap between classical logic based formalisms and logic programs Different logic-based knowledge representation formalisms have different limitations either with respect to expressivity or with respect to computational efficiency. First-order logic, which is the basis of Description Logics (DLs), is not suitable for defeasible reasoning due to its monotonic nature. The nonmonotonic formalisms that extend first-order logic, such as circumscription and default logic, are expressive but lack efficient implementations. The nonmonotonic formalisms that are based on the declarative logic programming approach, such as Answer Set Programming (ASP), have efficient implementations but are not expressive enough for representing and reasoning with open domains. This dissertation uses the first-order stable model semantics, which extends both first-order logic and ASP, to relate circumscription to ASP, and to integrate DLs and ASP, thereby partially overcoming the limitations of the formalisms. By exploiting the relationship between circumscription and ASP, well-known action formalisms, such as the situation calculus, the event calculus, and Temporal Action Logics, are reformulated in ASP. The advantages of these reformulations are shown with respect to the generality of the reasoning tasks that can be handled and with respect to the computational efficiency. The integration of DLs and ASP presented in this dissertation provides a framework for integrating rules and ontologies for the semantic web. This framework enables us to perform nonmonotonic reasoning with DL knowledge bases. Observing the need to integrate action theories and ontologies, the above results are used to reformulate the problem of integrating action theories and ontologies as a problem of integrating rules and ontologies, thus enabling us to use the computational tools developed in the context of the latter for the former.autPalla, RavithsLee, JoohyungdgcBaral, ChittadgcKambhampati, SubbaraodgcLifschitz, VladimirpblArizona State UniversityengPartial requirement for: Ph.D., Arizona State University, 2012Includes bibliographical references (p. 210-220)Field of study: Computer scienceby Ravi Pallahttps://hdl.handle.net/2286/R.I.1455700Doctoral DissertationAcademic thesesx, 220 p. : ill113458501701630349320150534adminIn CopyrightAll Rights Reserved2012TextComputer Scienceartificial intelligenceKnowledge Representation and ReasoningLogic programmingNonmonotonic reasoningReasoning about ActionsRules and OntologiesLogic programmingartificial intelligenceKnowledge representation (Information theory)Nonmonotonic reasoning