Until this book, possibly the only comprehensive treatment of planning has been a paper collection: Readings in Planning (Morgan Kaufmann Series in Representation and Reasoning). What these authors have done is phenominal - they've marshalled a bibliography of 565 publications into a comprehensive treatment from a common point of view. That makes it much easier to analyze different approaches to planning, as well as to see how various application domains have applied these approaches to solve real problems.The first 448 pages of the book discusses various planning approaches, from classical state-space planning including recent improvements in the STRIPS model (GraphPlan), to dealing with temporal operations and resource scheduling. They then use the readers understanding of these deterministic approaches to bridge to planning under uncertainty, which is where planning meets the "real world" of imperfect knowledge, observability or even actions having unintended effects. The next roughly 100 pages goes into application domains discussing how space applications, robotics, manufacturing, emergency evacuation and even the game of bridge has used these planning methods to give the reader better intuitions on their own domain.Finally some minority approaches such as case-based planning and plan related areas such as plan recognition are introduced briefly, leading to tutorial appendices on search (and complexity), first order logic, and model checking.I have been working on the periphery of planning research for over 25 years, including (currently) directing advanced research in adversarial planning (a topic not addressed by this book, but that's hardly surprising given the novelty of the approach ;-). This is the best overview and reference I've seen to date for this very important area.

Automated Planning: Theory & Practice (The Morgan Kaufmann Series in Artificial Intelligence) PDF

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