Intelligent Planning
A Decomposition and Abstraction Based Approach
Published on 28. September 2011
Book
Paperback/Softback
XXII, 252 pages
978-3-642-64477-1 (ISBN)
Description
"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.
More details
Series
Edition
Softcover reprint of the original 1st ed. 1997
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XXII, 252 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 16 mm
Weight
429 gr
ISBN-13
978-3-642-64477-1 (9783642644771)
DOI
10.1007/978-3-642-60618-2
Schweitzer Classification
Other editions
Additional editions
Book
10/1997
1st Edition
Springer
€85.55
Article exhausted; check different version
Persons
Charles Ling has been a professor at the Western University in Canada since 1989. He obtained his BSc. in Computer Science from the Shanghai Jiaotong University in 1985, and then graduated with his Masters and then Ph.D. in Computer Science from the University of Pennsylvania, USA, in 1987 and 1989, respectively. He specializes in data mining and machine learning, and their applications in Internet, business, healthcare, and bioinformatics. Overall, he has published over 120 research papers in peer-reviewed conferences and journals. Charles Ling has also engaged in much professional service in the above areas. He has been an associate editor for several top journals and an organizer for several top conferences in computer science. He is also a Senior Member of IEEE and a Lifetime Member of AAAI (Association of Advancement of Artificial Intelligence). Charles Ling is the director of the Data Mining and Business Intelligence Lab at Western University, where has been involved in several technology transfer projects. Charles Ling is also a specialist in child gifted education. He integrates his research in Artificial Intelligence and cognitive science, and develops a full range of thinking strategies that improve children's intellectual abilities. These thinking strategies embrace, enhance, and connect with math, science, and other areas.
Content
1. Introduction.- 1.1 The Problem.- 1.2 Key Issues.- 1.3 Planning Versus Scheduling.- 1.4 Contributions and Organization.- 1.5 Background.- I. Representation, Basic Algorithms, and Analytical Techniques.- 2. Representation and Basic Algorithms.- 3. Analytical Techniques.- 4. Useful Supporting Algorithms.- 5. Case Study: Collective Resource Reasoning.- II. Problem Decomposition and Solution Combination.- 6. Planning by Decomposition.- 7. Global Conflict Resolution.- 8. Plan Merging.- 9. Multiple-Goal Plan Selection.- III. Hierarchical Abstraction.- 10. Hierarchical Planning.- 11. Generating Abstraction Hierarchies.- 12. Properties of Task Reduction Hierarchies.- 13. Effect Abstraction.- References.