Intelligent Planning : A Decomposition and Abstraction Based Approach

Qiang Yang

ISBN 10: 3642644775 / ISBN 13: 9783642644771

Verlag: Springer Berlin Heidelberg, 2011

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 'The central fact is that we are planning agents.' (M. Bratman, Intentions, Plans, and Practical Reasoning, 1987, p. 2) Recent arguments to the contrary notwithstanding, it seems to be the case that people-the best exemplars of general intelligence that we have to date do a lot of planning. It is therefore not surprising that modeling the planning process has always been a central part of the Artificial Intelligence enterprise. Reasonable behavior in complex environments requires the ability to consider what actions one should take, in order to achieve (some of) what one wants and that, in a nutshell, is what AI planning systems attempt to do. Indeed, the basic description of a plan generation algorithm has remained constant for nearly three decades: given a desciption of an initial state I, a goal state G, and a set of action types, find a sequence S of instantiated actions such that when S is executed instate I, G is guaranteed as a result. Working out the details of this class of algorithms, and making the elabora tions necessary for them to be effective in real environments, have proven to be bigger tasks than one might have imagined.

Bestandsnummer des Verkäufers 9783642644771

Bibliografische Details

• Titel: Intelligent Planning : A Decomposition and Abstraction Based Approach
• Verlag: Springer Berlin Heidelberg
• Erscheinungsjahr: 2011
• Sprache: Englisch
• ISBN-10: 3642644775
• ISBN-13: 9783642644771
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

This monograph on AI planning is both a textbook and a general reference book. Assuming only minimal reader knowledge, it will interest not only seasoned researchers but also students and researchers in other fields.

Von der hinteren Coverseite

This monograph on planning based on Artificial Intelligence methods may serve both as an advanced textbook and as a general reference book. AI planning is an active research and applications field concerned with action and plan representation, plan synthesis and reasoning, analysis of planning algorithms, plan execution and monitoring, and plan reuse and learning.
The book provides a clear, thorough coverage of key areas of classical AI planning. Its main theme is to build more intelligence on a set of basic algorithms and representations for planning. It presents advanced techniques for plan generation using decomposition and plan merging and for analyzing and comparing planning algorithms. The book contains illustrations, examples, algorithms, analyses, tables, and extensive references.