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Automated Planning

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Automated Planning

Malik Ghallab, LAAS-CNRS, Dana Nau, Paolo Traverso, ITC-IRST

ISBN 1558608567
Pages 635

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 beyond classical planning, to include temporal planning, resource scheduling, planning under uncertainty, and modern techniques for plan generation, such as task decomposition, propositional satisfiability, constraint satisfaction, and model checking.

The authors combine over 30 years experience in planning research and development to offer an invaluable text to researchers, professionals, and graduate students.

*Comprehensively explains paradigms for automated planning.
*Provides a thorough understanding of theory and planning practice, and how they relate to each other.
*Presents case studies of applications in space, robotics, CAD/CAM, process control, emergency operations, and games.

1 Introduction and Overview I Classical Planning 2 Representations for Classical Planning 3 Complexity of Classical Planning 4 State-Space Planning 5 Plan-Space Planning II Neoclassical Planning 6 Planning-Graph Techniques 7 Propositional Satisfiability Techniques 8 Constraint Satisfaction Techniques III Heuristics and Control Strategies 9 Heuristics in Planning 10 Control Rules in Planning 11 Hierarchical Task Network Planning 12 Control Strategies in Deductive Planning IV Planning with Time and Resources 13 Time for Planning 14 Temporal Planning 15 Planning and Resource Scheduling V Planning under Uncertainty 16 Planning based on Markov Decision Processes 17 Planning based on Model Checking 18 Uncertainty with Neo-Classical Techniques VI Case Studies and Applications 19 Space Applications 20 Planning in Robotics 21 Planning for Manufacturability Analysis 22 Emergency Evacuation Planning 23 Planning in the Game of Bridge VII Conclusion 24 Conclusion and Other Topics VIII Appendices A Search Procedures and Computational Complexity B First Order Logic C Model Checking