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.In Section 2.3.1, many examples for extracting [f](A) belong to the inclusion principle. Combination principle ... a1={a set of squares}, a2={a set of rectangles}, a3={a set of diamonds}, a 4={a set of parallel quadrilaterals}, ... Let f(a1)={four edgesanbsp;...

Title | : | Quotient Space Based Problem Solving |

Author | : | Ling Zhang, Bo Zhang |

Publisher | : | Newnes - 2014-01-30 |

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