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An introduction to constraint-based temporal reasoning /

By: Barták, Roman [author.].
Contributor(s): Morris, Robert A [author.] | Venable, Kristen Brent [author.].
Material type: materialTypeLabelBookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on artificial intelligence and machine learning: # 26.Publisher: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.Description: 1 PDF (xiii, 107 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9781608459681.Subject(s): Constraints (Artificial intelligence) | Scheduling -- Data processing | Time -- Data processing | temporal reasoning | constraints | scheduling | planning | uncertainty | preferences | applications of temporal reasoningDDC classification: 006.3 Online resources: Abstract with links to resource | Abstract with links to full text Also available in print.
Contents:
Bibliography -- Authors' biographies.
4. Applications of temporal reasoning -- 4.1 Introduction -- 4.2 Activity planning -- 4.2.1 Constraint-based planning -- 4.2.2 Example plan -- 4.2.3 Fixed vs. flexible plans -- 4.3 Autonomous execution for space exploration systems -- 4.3.1 Remote agent executive -- 4.3.2 Reactive model-based programming language (RMPL) -- 4.4 Extracting temporal information from data -- 4.4.1 Real time situation recognition/monitoring -- 4.4.2 3D reconstructions of image data -- 4.4.3 Detecting temporal patterns in large medical data sets -- 4.4.4 Temporal information extraction from natural language text -- 4.5 Summary --
3. Extensions: preferences and uncertainty -- 3.1 Preferences -- 3.1.1 Preferences in qualitative frameworks -- 3.1.2 Preferences in quantitative frameworks -- 3.1.3 Simple temporal problems with preferences (STPPs) -- 3.1.4 Other extensions -- 3.2 Uncertainty -- 3.2.1 Simple temporal problems with uncertainty -- 3.2.2 Controllability -- 3.2.3 Conditional temporal problems -- 3.2.4 Conditional simple temporal networks with uncertainty -- 3.3 Combining preferences and uncertainty -- 3.3.1 Simple temporal problems with preferences and uncertainty -- 3.3.2 Conditional temporal problems with preferences -- 3.4 Summary --
2. Temporal frameworks based on constraints -- 2.1 Qualitative temporal frameworks -- 2.1.1 Point algebra -- 2.1.2 Interval algebra -- 2.1.3 Tractability of specific interval algebras and relation to the point algebra -- 2.1.4 Historical context -- 2.2 Quantitative temporal frameworks -- 2.2.1 Simple temporal problems -- 2.2.2 Temporal constraint satisfaction problems -- 2.2.3 Disjunctive temporal problems -- 2.2.4 Temporal networks with alternatives -- 2.2.5 Historical context -- 2.3 Relations between qualitative and quantitative frameworks -- 2.4 Summary --
1. Introduction to time in AI systems -- 1.1 The rise of time management: planning and scheduling -- 1.2 Logical and mathematical formulations -- 1.2.1 Mathematical formulations -- 1.2.2 Logical and philosophical frameworks -- 1.2.3 Origins of time in AI systems -- 1.3 Time granularity -- 1.4 Time and agent architectures -- 1.4.1 Example -- 1.4.2 Overview of remainder of book --
Abstract: Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. This book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. The book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. This book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems.
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBKE553
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System requirements: Adobe Acrobat Reader.

Mode of access: World Wide Web.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (pages 95-105).

Bibliography -- Authors' biographies.

4. Applications of temporal reasoning -- 4.1 Introduction -- 4.2 Activity planning -- 4.2.1 Constraint-based planning -- 4.2.2 Example plan -- 4.2.3 Fixed vs. flexible plans -- 4.3 Autonomous execution for space exploration systems -- 4.3.1 Remote agent executive -- 4.3.2 Reactive model-based programming language (RMPL) -- 4.4 Extracting temporal information from data -- 4.4.1 Real time situation recognition/monitoring -- 4.4.2 3D reconstructions of image data -- 4.4.3 Detecting temporal patterns in large medical data sets -- 4.4.4 Temporal information extraction from natural language text -- 4.5 Summary --

3. Extensions: preferences and uncertainty -- 3.1 Preferences -- 3.1.1 Preferences in qualitative frameworks -- 3.1.2 Preferences in quantitative frameworks -- 3.1.3 Simple temporal problems with preferences (STPPs) -- 3.1.4 Other extensions -- 3.2 Uncertainty -- 3.2.1 Simple temporal problems with uncertainty -- 3.2.2 Controllability -- 3.2.3 Conditional temporal problems -- 3.2.4 Conditional simple temporal networks with uncertainty -- 3.3 Combining preferences and uncertainty -- 3.3.1 Simple temporal problems with preferences and uncertainty -- 3.3.2 Conditional temporal problems with preferences -- 3.4 Summary --

2. Temporal frameworks based on constraints -- 2.1 Qualitative temporal frameworks -- 2.1.1 Point algebra -- 2.1.2 Interval algebra -- 2.1.3 Tractability of specific interval algebras and relation to the point algebra -- 2.1.4 Historical context -- 2.2 Quantitative temporal frameworks -- 2.2.1 Simple temporal problems -- 2.2.2 Temporal constraint satisfaction problems -- 2.2.3 Disjunctive temporal problems -- 2.2.4 Temporal networks with alternatives -- 2.2.5 Historical context -- 2.3 Relations between qualitative and quantitative frameworks -- 2.4 Summary --

1. Introduction to time in AI systems -- 1.1 The rise of time management: planning and scheduling -- 1.2 Logical and mathematical formulations -- 1.2.1 Mathematical formulations -- 1.2.2 Logical and philosophical frameworks -- 1.2.3 Origins of time in AI systems -- 1.3 Time granularity -- 1.4 Time and agent architectures -- 1.4.1 Example -- 1.4.2 Overview of remainder of book --

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. This book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. The book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. This book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems.

Also available in print.

Title from PDF title page (viewed on March 14, 2014).

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