EAN: 9783031004360

SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE A...

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 Contents: Preface
Planning and Autonomous Behavior   Classical Planning: Full Information and Deterministic
Actions   Classical Planning: Variations and Extensions   Beyond Classical Planning:
Transformations   Planning with Sensing: Logical Models   MDP Planning: Stochastic Actions and
Full Feedback   POMDP Planning: Stochastic Actions and Partial Feedback   Discussion  
Bibliography   Author's Biography

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