Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing

Quotient Space Based Problem Solving provides an in-depth treatment of hierarchical problem solving, computational complexity, and the principles and applications of multi-granular computing, including inference, information fusing, planning, and heuristic search. Drawing upon years of academic research and using numerous examples and illustrative applications, the authors, Ling Zhang and Bo Zhang provide a unique guide to computerized problem solving and granular computing. This book is a valuable guide to graduate students, research fellows, and academics specializing in artificial intelligence or concerned with computerized problem solving and granular computing. Explains the theory of hierarchical problem solving, its computational complexity, and discusses the principle and applications of multi-granular computing Describes a human-like, theoretical framework using quotient space theory, that will be of interest to researchers in artificial intelligence. Provides many applications and examples in the engineering and computer science area. Includes complete coverage of planning, heuristic search and coverage of strictly mathematical models. INDICE: Chapter 1 Problem Representation Chapter 2 Hierarchy and Multi-granular Computing Chapter 3 Information Synthesis in Multi-granular Computing Chapter 4 Reasoning in Multi-granular Computing Chapter 5 Automatic Spatial Planning Chapter 6 Statistical Heuristic Search Chapter 7 the Expansion of Quotient Space Theory Addenda A: Some Concepts and Properties of Point Set Topology Addenda B: Some Concepts and Properties of Integral and Statistical Inference

• ISBN: 978-0-12-410387-0
• Editorial: Morgan Kaufmann
• Encuadernacion: Cartoné
• Páginas: 352
• Fecha Publicación: 10/04/2014
• Nº Volúmenes: 1
• Idioma: Inglés