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.