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Situation Theory grew out of attempts by Jon Barwise in the late 1970s to provide a semantics for 'naked-infinitive' perceptual reports such as 'Claire saw Jon run'. Barwise's intuition was that Claire didn't just see Jon, an individual, but Jon doing something, a situation. Situations are individuals having properties and standing in relations. A theory of situations would allow us to study and compare various types of situations or situation-like entitles, such as facts, events, and scenes. One of the central themes of situation theory of meaning and reference should be set within a general theory of information, one moreover that is rich enough to do justice to perception, communication, and thought. By now many people have contributed by the need to give a rigorous mathematical account of the principles of information that underwrite the theory.
Situation theory is the result of an interdisciplinary effort to create a full-fledged theory of information. Created by scholars and scientists from cognitive science, computer science, AI, linguistics, logic, philosophy, and mathematics, the theory is forging a common set of tools for the analysis of phenomena from all these fields. This volume presents work that evolved out of the Second Conference on Situation Theory and its Applications. Twenty-six essays exhibit the wide range of the theory, covering such topics as natural language semantics, philosophical issues about information, mathematical applications, and the visual representation of information in computer systems.Jon Barwise is a professor of philosophy, mathematics, and logic at Indiana University in Bloomington. Jean Mark Gawron is a researcher at SRI International and a consultant at Hewlett-Packard Laboratories. Gordon Plotkin is a professor of theoretical computer science at the University of Edinburgh. Syun Tutiya is in the philosophy department at Chiba University in Japan.
Situation theory is the result of an interdisciplinary effort to create a full-fledged theory of information. Created by scholars and scientists from cognitive science, computer science and AI, linguistics, logic, philosophy, and mathematics, it aims to provide a common set of tools for the analysis of phenomena from all these fields. Unlike Shannon-Weaver type theories of information, which are purely quantitative theories, situation theory aims at providing tools for the analysis of the specific content of a situation (signal, message, data base, statement, or other information-carrying situation). The question addressed is not how much information is carried, but what information is carried.
The classic text for understanding complex statistical probability An Introduction to Probability Theory and Its Applications offers comprehensive explanations to complex statistical problems. Delving deep into densities and distributions while relating critical formulas, processes and approaches, this rigorous text provides a solid grounding in probability with practice problems throughout. Heavy on application without sacrificing theory, the discussion takes the time to explain difficult topics and how to use them. This new second edition includes new material related to the substitution of probabilistic arguments for combinatorial artifices as well as new sections on branching processes, Markov chains, and the DeMoivre-Laplace theorem.
Intelligence can be characterised both as the ability to absorb and process information and as the ability to reason. Humans and other animals have both of these abilities to a greater or lesser degree, but the search for artificial intelligence has been hampered by our inability to create a theory that covers both of these characteristics. In this provocative and ground-breaking book, Professor Keith Devlin argues that to obtain a deeper understanding of the nature of intelligence and knowledge acquisition, we must broaden our concept of logic. For these purposes, Devlin introduces the concept of the infon, a quantum of information, and merges it with situations, a mathematical construction generalising the notion of sets developed by Barwise and Perry at Stanford University in order to study the meaning of natural languages. He develops and describes the theory here in general and intuitive terms, and discusses its relevance to a variety of concerns such as artificial intelligence, cognition, natural language and communication.
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Intensional logic has emerged, since the 1960' s, as a powerful theoretical and practical tool in such diverse disciplines as computer science, artificial intelligence, linguistics, philosophy and even the foundations of mathematics. The present volume is a collection of carefully chosen papers, giving the reader a taste of the frontline state of research in intensional logics today. Most papers are representative of new ideas and/or new research themes. The collection would benefit the researcher as well as the student. This book is a most welcome addition to our series. The Editors CONTENTS PREFACE IX JOHAN VAN BENTHEM AND NATASHA ALECHINA Modal Quantification over Structured Domains PATRICK BLACKBURN AND WILFRIED MEYER-VIOL Modal Logic and Model-Theoretic Syntax 29 RUY J. G. B. DE QUEIROZ AND DOV M. GABBAY The Functional Interpretation of Modal Necessity 61 VLADIMIR V. RYBAKOV Logics of Schemes for First-Order Theories and Poly-Modal Propositional Logic 93 JERRY SELIGMAN The Logic of Correct Description 107 DIMITER VAKARELOV Modal Logics of Arrows 137 HEINRICH WANSING A Full-Circle Theorem for Simple Tense Logic 173 MICHAEL ZAKHARYASCHEV Canonical Formulas for Modal and Superintuitionistic Logics: A Short Outline 195 EDWARD N. ZALTA 249 The Modal Object Calculus and its Interpretation NAME INDEX 281 SUBJECT INDEX 285 PREFACE Intensional logic has many faces. In this preface we identify some prominent ones without aiming at completeness.
Concise Encyclopedia of Semantics is a comprehensive new reference work aiming to systematically describe all aspects of the study of meaning in language. It synthesizes in one volume the latest scholarly positions on the construction, interpretation, clarification, obscurity, illustration, amplification, simplification, negotiation, contradiction, contraction and paraphrasing of meaning, and the various concepts, analyses, methodologies and technologies that underpin their study. It examines not only semantics but the impact of semantic study on related fields such as morphology, syntax, and typologically oriented studies such as 'grammatical semantics', where semantics has made a considerable contribution to our understanding of verbal categories like tense or aspect, nominal categories like case or possession, clausal categories like causatives, comparatives, or conditionals, and discourse phenomena like reference and anaphora. COSE also examines lexical semantics and its relation to syntax, pragmatics, and cognitive linguistics; and the study of how 'logical semantics' develops and thrives, often in interaction with computational linguistics. As a derivative volume from Encyclopedia of Language and Linguistics, Second Edition, it comprises contributions from 150 of the foremost scholars of semantics in their various specializations and draws on 20+ years of development in the parent work in a compact and affordable format. Principally intended for tertiary level inquiry and research, this will be invaluable as a reference work for undergraduate and postgraduate students as well as academics inquiring into the study of meaning and meaning relations within languages. As semantics is a centrally important and inherently cross-cutting area within linguistics it will therefore be relevant not just for semantics specialists, but for most linguistic audiences. - The first encyclopedia ever published in this fascinating and diverse field - Combines the talents of the world's leading semantics specialists - The latest trends in the field authoritatively reviewed and interpreted in context of related disciplines - Drawn from the richest, most authoritative, comprehensive and internationally acclaimed reference resource in the linguistics area - Compact and affordable single volume reference format
The logical study of language is becoming more interdisciplinary, playing a role in fields such as computer science, artificial intelligence, cognitive science and game theory. This new edition, written by the leading experts in the field, presents an overview of the latest developments at the interface of logic and linguistics as well as a historical perspective. It is divided into three parts covering Frameworks, General Topics and Descriptive Themes. - Completely revised and updated - includes over 25% new material - Discusses the interface between logic and language - Many of the authors are creators or active developers of the theories
In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.