Automated Planning: Theory and Practice

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.

Provides a thorough understanding of AI planning theory and practice, and how they relate to each otherCovers all the contemporary topics of planning, as well as important practical applications of planning, such as model checking and game playingPresents case studies and applications in planning engineering, space, robotics, CAD/CAM, process control, emergency operations, and gamesProvides lecture notes, examples of programming assignments, pointers to downloadable planning systems and related information online

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