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Reasoning Systems (reasoning + system)
Selected AbstractsStrategies in Human Nonmonotonic ReasoningCOMPUTATIONAL INTELLIGENCE, Issue 3 2000Marilyn Ford Although humans seem adept at drawing nonmonotonic conclusions, the nonmonotonic reasoning systems that researchers develop are complex and do not function with such ease. This paper explores people's reasoning processes in nonmonotonic problems. To avoid the problem of people's conclusions being based on knowledge rather than on some reasoning process, we developed a scenario about life on another planet. Problems were chosen to allow the systematic study of people's understanding of strict and nonstrict rules and their interactions. We found that people had great difficulty reasoning and we identified a number of negative factors influencing their reasoning. We also identified three positive factors which, if used consistently, would yield rational and coherent reasoning,but no subject achieved total consistency. (Another possible positive factor, specificity, was considered but we found no evidence for its use.) It is concluded that nonmonotonic reasoning is hard. When people need to reason in a domain where they have no preconceived ideas, the foundation for their reasoning is neither coherent nor rational. They do not use a nonmonotonic reasoning system that would work regardless of content. Thus, nonmonotonic reasoning systems that researchers develop are expected to do more reasoning than humans actually do! [source] A framework for linguistic logic programmingINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 6 2010Tru H. Cao Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real-world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD-style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc. [source] A stratified first order logic approach for access controlINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 9 2004Salem Benferhat Modeling information security policies is an important problem in many domains. This is particularly true in the health care sector, where information systems often manage sensitive and critical data. This article proposes to use nonmonotonic reasoning systems to control access to sensitive data in accordance with a security policy. In the first part of the article, we propose an access control model that overcomes several limitations of existing systems. In particular, it allows us to deal with contexts and to represent the two main kinds of privileges: permissions and prohibitions. This model will then be formally encoded using stratified (or prioritized) first-order knowledge bases. In the second part of the article, we discuss the problem of conflicts due to the joint handling of permissions and prohibitions. We show that approaches proposed for solving conflicts in propositional knowledge bases are not appropriate for handling inconsistent first-order knowledge bases. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 817,836, 2004. [source] Defeasible logic with dynamic prioritiesINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 5 2004Grigoris Antoniou Defeasible logic is a nonmonotonic reasoning approach based on rules and priorities. Its design supports efficient implementation, and it shows promise to be deployed successfully in applications. So far, only static priorities have been used, provided by an external superiority relation. In this article we show how dynamic priorities can be integrated, where priority information is obtained from the deductive process itself. Dynamic priorities have been studied for other related reasoning systems such as default logic and argumentation. We define a proof theory, study its formal properties, and provide an argumentation semantics. © 2004 Wiley Periodicals, Inc. [source] |