الصفحة 1
الصفحة 1
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Handbook of philosophical logic ; Vol. 14

I would like to take this opportunity to put forward my current views about logic in computer science, computational linguistics and arti?cial intelligence. In the early 1980s the perception of the role of logic in computer science was that of a speci?cation and reasoning tool and that of a basis for possibly neat computer languages. The computer scientist was manipulating data structures and the use of logic was one of his options.

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Game-Theoretical Semantics : Essays on Semantics by Hintikka, Carlson, Peacocke, Rantala and Saarinen

This book is a collection of studies applying game-theoretical concepts and ideas to analysing the semantics of natural language and some formal languages. The bulk of the book consists of several papers by Hintikka, Carlson and Saarinen and discusses several of the central problems of the semantics of natural language.The topics covered are the semantics of natural language quantifiers, conditionals, pronouns and anaphora more generally. Hintikka’s famous essay presenting examples of "branching quantifier structures" in English, as well as one formulating his "any-every thesis", are included. The book also includes Hintikka’s closely argued philosophical discussion of the relationships between the new semantical games with the language games of Wittgenstein.

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Conditionals, Information, and Inference

Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false — rather, a conditional “if A then B” provides a context, A, for B to be plausible (or true) and must not be confused with “A entails B” or with the material implication “not A or B.” This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The ?rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti?cial Intelligence made claims for appropriate formaltoolstohandle“generalizedrules.”Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision.

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Attitudes and changing contexts

In this book, the author defends a unified externalists account of propositional attitudes and reference, and formalizes this view within possible world semantics.

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