Quotient Space Based Problem Solving
A Theoretical Foundation of Granular Computing
Nonfiction, Computers, Advanced Computing, Natural Language Processing, Artificial Intelligence, Reference & Language, Language Arts
| Author: | Ling Zhang, Bo Zhang | ISBN: | 9780124104433 |
| Publisher: | Elsevier Science | Publication: | January 30, 2014 |
| Imprint: | Morgan Kaufmann | Language: | English |
| Author: | Ling Zhang, Bo Zhang |
| ISBN: | 9780124104433 |
| Publisher: | Elsevier Science |
| Publication: | January 30, 2014 |
| Imprint: | Morgan Kaufmann |
| Language: | English |
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.
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Explains the theory of hierarchical problem solving, its computational complexity, and discusses the principle and applications of multi-granular computing
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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
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.
-
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
