Synopses & Reviews
Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community.
This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.
Review
This book is a masterful integration of several decades of work on first-order logic, situation calculus, logic programming, and semantics of time and knowledge. The result is a unified, well-thought-out, and systematic approach to dynamical systems that spans much of modern computer science and AI. The MIT Press
Review
This book describes a thoroughly developed logic- and situation-calculus-based system for problem solving and planning. Its emphasis on theory is especially important for the ambitious student who wants to look beyond immediate applications toward the goal of human-level artificial intelligence. Johan van Benthem, University of Amsterdam
Review
"This outstanding work should be on the shelf of anyone concerned with logical control of physical processes."--Anil Nerode, Goldwin Smith Professor of Mathematics, Cornell University The MIT Press
Review
"Human cognition sparkles brightest in the theatre of communication. This book takes you there the 'Edinburgh Way': that is, with a sound mix of psychology, logic, linguistics, computer science, and always-lively philosophical debate."--Johan van Benthem, University of Amsterdam The MIT Press
Review
This outstanding work should be on the shelf of anyone concerned with logical control of physical processes. John McCarthy, Professor Emeritus of Computer Science, Stanford University
Synopsis
Specifying and implementing dynamical systems with the situation calculus.
Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community.
This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.
Synopsis
Specifying and implementing dynamical systems with the situation calculus.
Synopsis
This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.
Synopsis
Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community.
Description
Includes bibliographical references (p. [409]-418) and index.
About the Author
Raymond Reiter is Professor and Co-Director of the Cognitive Robotics Project in the Department of Computer Science at the University of Toronto.