By Michael Negnevitsky
Synthetic Intelligence is without doubt one of the so much swiftly evolving topics in the computing/engineering curriculum, with an emphasis on growing useful purposes from hybrid innovations. regardless of this, the conventional textbooks proceed to count on mathematical and programming services past the scope of present undergraduates and concentrate on parts no longer proper to a lot of today's classes. Negnevitsky exhibits scholars find out how to construct clever platforms drawing on thoughts from knowledge-based structures, neural networks, fuzzy platforms, evolutionary computation and now additionally clever brokers. the rules at the back of those recommendations are defined with no resorting to advanced arithmetic, displaying how some of the options are carried out, once they are precious and after they usually are not. No specific programming language is thought and the e-book doesn't tie itself to any of the software program instruments on hand. despite the fact that, to be had instruments and their makes use of should be defined and software examples may be given in Java. the shortcoming of assumed previous wisdom makes this publication perfect for any introductory classes in man made intelligence or clever platforms layout, whereas the contempory insurance ability extra complicated scholars will profit by way of researching the most recent state of the art ideas.
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Extra info for Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition)
The operator identifies the object and assigns the value. Operators such as is, are, is not, are not are used to assign a symbolic value to a linguistic object. But expert systems can also use mathematical operators to define an object as numerical and assign it to the numerical value. For example, IF ‘age of the customer’ < 18 AND ‘cash withdrawal’ > 1000 THEN ‘signature of the parent’ is required Similar to a rule antecedent, a consequent combines an object and a value connected by an operator.
Fuzzy logic or fuzzy set theory was introduced by Professor Lotfi Zadeh, Berkeley’s electrical engineering department chairman, in 1965 (Zadeh, 1965). It provided a means of computing with words. However, acceptance of fuzzy set theory by the technical community was slow and difficult. Part of the problem was the provocative name – ‘fuzzy’ – which seemed too light-hearted to be taken seriously. Eventually, fuzzy theory, ignored in the West, was taken seriously in the East – by the Japanese. It has been used successfully since 1987 in Japanese-designed dishwashers, washing machines, air conditioners, television sets, copiers and even cars.
1. The domain expert is a knowledgeable and skilled person capable of solving problems in a specific area or domain. This person has the greatest expertise in a given domain. This expertise is to be captured in the expert system. Therefore, the expert must be able to communicate his or her knowledge, be willing to participate in the expert system development and commit a substantial amount of time to the project. The domain expert is the most important player in the expert system development team.
Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition) by Michael Negnevitsky