Zhongzhi Shi's Advanced Artificial Intelligence (Series on Intelligence PDF

By Zhongzhi Shi

ISBN-10: 981429134X

ISBN-13: 9789814291347

Man made intelligence is a department of machine technological know-how and a self-discipline within the research of computer intelligence, that's, constructing clever machines or clever structures imitating, extending and augmenting human intelligence via synthetic capacity and methods to gain clever habit. complex man made Intelligence involves sixteen chapters. The content material of the booklet is novel, displays the study updates during this box, and particularly summarizes the author's medical efforts over a long time. The publication discusses the tools and key know-how from conception, set of rules, process and functions concerning man made intelligence. This booklet might be considered as a textbook for senior scholars or graduate scholars within the info box and comparable tertiary specialities. it's also compatible as a reference ebook for correct medical and technical body of workers.

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Additional resources for Advanced Artificial Intelligence (Series on Intelligence Science)

Sample text

Taken these rules and facts as inputs of the Prolog engine, we can compile and execute it. - Son(Y,X), we will get the result Son(xiao-li, lao-li). 2 Data structure and recursion in Prolog An important and powerful tool in problem solving and programming, recursion is extensively used in data structures and programs of Prolog. Term is a basic data structure in Prolog. Everything including program and data is expressed in form of term. Terms of Prolog are defined recursively by the following BNF rule: ::= | | |() where structures are also called compound terms, and are generated by the BNF rule: 36 Advanced Artificial Intelligence ::= {, }) ::= List is an important data structure supported by Prolog.

During the SLD resolution process, in the case that a clause which contains a cut-fail composition is examined for resolution, resolution of the father-goal of the CUT predication will be finished directly. Therefore, efficiency of search will be increased. For example, consider the following program P: (1) strong(X):- heart_disease(X), fail. (2) strong(X):- tuberculosis(X), fail. (3) strong(X):- nearsight(X), fail. (4) (5) strong(X). heart_disease(Zhang). - strong(Zhang)” be the goal. According to the first clause of program P, the goal “strong(Zhang)” can be first unified with a resolvent “heart_disease(Zhang), fail”; then a backtracking will be triggered by the “fail” after the unification of “heart_disease(Zhang)”.

We can reduce the backtracking according to place a CUT prior to the “fail” occurring in the P. , fail. , fail. , fail. Then, according to first clause of the program, a backtracking will be triggered by the “fail” after the unification of the goal “strong(Zhang)” and unification of the new generated sub-goal “heart_disease(Zhang)”. Since “strong(Zhang)” is the father-goal of the CUT that contained in the first clause of P, it will be poped from the goal stack also. Therefore, the SLD resolution will be finished right away and return a negative result.

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Advanced Artificial Intelligence (Series on Intelligence Science) by Zhongzhi Shi


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