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.
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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.
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.
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Taschenbuch. Zustand: Neu. 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. Artikel-Nr. 9783642644771
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Taschenbuch. Zustand: Neu. Intelligent Planning | A Decomposition and Abstraction Based Approach | Qiang Yang | Taschenbuch | Artificial Intelligence | xxii | Englisch | 2011 | Springer | EAN 9783642644771 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 106367671
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