05531nam 22006734a 450 991045050280332120200520144314.01-281-00721-897866110072180-08-049051-4(CKB)1000000000016240(EBL)333985(OCoLC)156908421(SSID)ssj0000107939(PQKBManifestationID)11135221(PQKBTitleCode)TC0000107939(PQKBWorkID)10016023(PQKB)11045633(MiAaPQ)EBC333985(Au-PeEL)EBL333985(CaPaEBR)ebr10226616(CaONFJC)MIL100721(EXLCZ)99100000000001624020031223d2004 uy 0engur|n|---|||||txtccrAutomated planning[electronic resource] theory and practice /Ghallab Malik, Dana Nau, Paolo TraversoAmsterdam ;Boston Elsevier/Morgan Kaufmannc20041 online resource (664 p.)The Morgan Kaufmann Series in Artificial IntelligenceDescription based upon print version of record.1-4933-0370-8 1-55860-856-7 Includes bibliographical references (p. 573-607) and index.Front Cover; Automated Planning Theory and Practice; Copyright Page; Contents; About the Authors; Foreword; Preface; Table of Notation; Chapter 1. Introduction and Overview; 1.1 First Intuitions on Planning; 1.2 Forms of Planning; 1.3 Domain-Independent Planning; 1.4 Conceptual Model for Planning; 1.5 Restricted Model; 1.6 Extended Models; 1.7 A Running Example: Dock-Worker Robots; Part I: Classical Planning; Chapter 2. Representations for Classical Planning; 2.1 Introduction; 2.2 Set-Theoretic Representation; 2.3 Classical Representation; 2.4 Extending the Classical Representation2.5 State-Variable Representation2.6 Comparisons; 2.7 Discussion and Historical Remarks; 2.8 Exercises; Chapter 3. Complexity of Classical Planning; 3.1 Introduction; 3.2 Preliminaries; 3.3 Decidability and Undecidability Results; 3.4 Complexity Results; 3.5 Limitations; 3.6 Discussion and Historical Remarks; 3.7 Exercises; Chapter 4. State-Space Planning; 4.1 Introduction; 4.2 Forward Search; 4.3 Backward Search; 4.4 The STRIPS Algorithm; 4.5 Domain-Specific State-Space Planning; 4.6 Discussion and Historical Remarks; 4.7 Exercises; Chapter 5. Plan-Space Planning; 5.1 Introduction5.2 The Search Space of Partial Plans5.3 Solution Plans; 5.4 Algorithms for Plan-Space Planning; 5.5 Extensions; 5.6 Plan-Space versus State-Space Planning; 5.7 Discussion and Historical Remarks; 5.8 Exercises; Part II: Neoclassical Planning; Chapter 6. Planning-Graph Techniques; 6.1 Introduction; 6.2 Planning Graphs; 6.3 The Graphplan Planner; 6.4 Extensions and Improvements of Graphplan; 6.5 Discussion and Historical Remarks; 6.6 Exercises; Chapter 7. Propositional Satisfiability Techniques; 7.1 Introduction; 7.2 Planning Problems as Satisfiability Problems; 7.3 Planning by Satisfiability7.4 Different Encodings7.5 Discussion and Historical Remarks; 7.6 Exercises; Chapter 8. Constraint Satisfaction Techniques; 8.1 Introduction; 8.2 Constraint Satisfaction Problems; 8.3 Planning Problems as CSPs; 8.4 CSP Techniques and Algorithms; 8.5 Extended CSP Models; 8.6 CSP Techniques in Planning; 8.7 Discussion and Historical Remarks; 8.8 Exercises; Part III: Heuristics and Control Strategies; Chapter 9. Heuristics in Planning; 9.1 Introduction; 9.2 Design Principle for Heuristics: Relaxation; 9.3 Heuristics for State-Space Planning; 9.4 Heuristics for Plan-Space Planning9.5 Discussion and Historical Remarks9.6 Exercises; Chapter 10. Control Rules in Planning; 10.1 Introduction; 10.2 Simple Temporal Logic; 10.3 Progression; 10.4 Planning Procedure; 10.5 Extensions; 10.6 Extended Goals; 10.7 Discussion and Historical Remarks; 10.8 Exercises; Chapter 11. Hierarchical Task Network Planning; 11.1 Introduction; 11.2 STN Planning; 11.3 Total-Order STN Planning; 11.4 Partial-Order STN Planning; 11.5 HTN Planning; 11.6 Comparisons; 11.7 Extensions; 11.8 Extended Goals; 11.9 Discussion and Historical Remarks; 11.10 ExercisesChapter 12. Control Strategies in Deductive PlanningAutomated planning technology now plays a significant role in a variety of demanding applications, ranging from controlling space vehicles and robots to playing the game of bridge. These real-world applications create new opportunities for synergy between theory and practice: observing what works well in practice leads to better theories of planning, and better theories lead to better performance of practical applications. Automated Planning mirrors this dialogue by offering a comprehensive, up-to-date resource on both the theory and practice of automated planning. The book goes well bThe Morgan Kaufmann Series in Artificial IntelligenceProduction planningData processingElectronic books.Production planningData processing.658.5Ghallab Malik289496Nau Dana S992897Traverso Paolo992898MiAaPQMiAaPQMiAaPQBOOK9910450502803321Automated planning2273623UNINA