Automated planning : theory and practice / / Ghallab Malik, Dana Nau, Paolo Traverso

• Record Nr.: UNINA9910827091803321
• Autore: Ghallab Malik
• Pubbl/distr/stampa: Amsterdam ; ; Boston, : Elsevier/Morgan Kaufmann, c2004
• ISBN: 1-281-00721-8; 9786611007218; 0-08-049051-4
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (664 p.)
• Collana: The Morgan Kaufmann Series in Artificial Intelligence
• Altri autori (Persone): NauDana S; TraversoPaolo
• Disciplina: 658.5
• Soggetti: Production planning - Data processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 573-607) and index.
• Nota di contenuto: 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 Representation; 2.5 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 Introduction; 5.2 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 Satisfiability; 7.4 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 Planning; 9.5 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 Exercises; Chapter 12. Control Strategies in Deductive Planning
• Sommario/riassunto: Automated 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 b