A Concise Introduction to Models and Methods for Automated Planning: Synthesis Lectures on Artificial Intelligence and Machine Learning

by Hector Geffner

Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective.
Table of Preface / Planning and Autonomous Behavior / Classical Full Information and Deterministic Actions / Classical Variations and Extensions / Beyond Classical Transformations / Planning with Logical Models / MDP Stochastic Actions and Full Feedback / POMDP Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography

142 pages, Paperback

First published April 1, 2013