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.

Key Features

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