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Epistemic Logic for AI and Computer Science

Epistemic logic has grown from its philosophical beginnings to find diverse applications in computer science as a means of reasoning about;

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Artificial Intelligence: Research Directions in Cognitive Science

programming and representation; machine learning; natural language; vision; the design of an AI programming environment; and medicine, a major;

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Artificial Intelligence: Research Directions in Cognitive Science

programming and representation; machine learning; natural language; vision; the design of an AI programming environment; and medicine, a major;

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Logical Foundations of Computer Science

logic and topological semantics; linear logic; epistemic and temporal logics; intelligent and multiple agent system logics; logics of proof and;

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Logical Foundations of Computer Science

rewriting; lambda and combinatory calculi; categorical logic and topological semantics; linear logic; epistemic and temporal logics; intelligent;

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Logical Foundations of Computer Science

; lambda and combinatory calculi; categorical logic and topological semantics; linear logic; epistemic and temporal logics; intelligent and;

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Logical Foundations of Computer Science

; lambda andcombinatory calculi; categorical logic and topological semantics; linear logic; epistemic and temporal logics; intelligent and multiple;

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Advances in Modal Logic Volume 9

papers. The topics include decidability and complexity results for specifi c modal logics, proof theory of modal logic, logics for reasoning;

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Advances in Modal Logic Volume 10

papers. The topics include decidability and complexity results for specifi c modal logics, proof theory of modal logic, logics for reasoning;

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Knowledge Proof and Dynamics

contributions cover a wide variety of topics in modal logic (epistemic logic, temporal logic and dynamic logic), proof theory, algebraic logic, game;

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Knowledge, Proof and Dynamics

contributions cover a wide variety of topics in modal logic (epistemic logic, temporal logic and dynamic logic), proof theory, algebraic logic, game;

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Uncertain Inference

of these approaches within a unified framework. The principal market for the book will be students and professionals in philosophy, computer;

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Uncertain Inference

of these approaches within a unified framework. The principal market for the book will be students and professionals in philosophy, computer;

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Artificial Intelligence

theory, probability, optimisation and logic. AI research also overlaps such fields as robotics, control systems, scheduling, data mining;

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Cambridge Tracts in Mathematics

truths. Justification logic is a theory of reasoning that enables the tracking of evidence for statements and therefore provides a logical;

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Guide to Deep Learning Basics

enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text;

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Perceptual Computing

is an important go-to for researchers and students in AI, fuzzy logic, computer science in general, and psychology.;

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Temporal Logic

temporal logic, gives a thorough state-of-the-art report on all aspects of temporal logic research relevant for computer science and AI. It;

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Logics for Computer and Data Sciences, and Artificial Intelligence

This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and;

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Logic for Computer Scientists

This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate;

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Contemporary Artificial Intelligence

Artificial Intelligence presents strong AI methods and algorithms for solving challenging problems involving systems that behave intelligently;

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Labelled Deduction

Labelled deduction is an approach to providing frameworks for presenting and using different logics in a uniform and natural way by;

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Essential Logic for Computer Science

rather than theory. Computer scientists use logic for testing and verification of software and digital circuits, but many computer science;

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Logic, Rationality, and Interaction

researchers from a variety of logic-related fields: Game and Decision Theory, Philosophy, Linguistics, Computer Science and AI. This year had a;

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Mathematical Logic and Theoretical Computer Science

and automated reasoning, stability theory, topoi and mathematics, and topoi and logic. It is intended for mathematical logicians and computer;

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Knowledge in Flux

a paper "Relations between the logic of theory change and nonmonotonic logic" by the author and David Makinson. The following describes the;

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Mathematical Logic and Theoretical Computer Science

Mathematical Logic and Theoretical Computer Science covers various topics ranging from recursion theory to Zariski topoi. Leading;

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