Expert System: Fundamentals and Applications for Teaching Computers to Think like Experts
Par šo e-grāmatu
In the field of artificial intelligence, an expert system is a type of computer program that simulates the abilities of a human expert to make judgment calls. Instead of using typical procedural code, expert systems reason through bodies of knowledge, which are primarily represented as if-then rules. This is in contrast to traditional computer programs, which tackle complicated issues by writing procedural code. In the 1970s, the first expert systems were developed, and later in the 1980s, their use became more widespread. Expert systems were one of the earliest forms of artificial intelligence (AI) software that was actually successful. An expert system can be broken down into its two component subsystems, which are the knowledge base and the inference engine. The knowledge base is a collection of facts and guidelines. The inference engine takes the rules and applies them to the known data in order to derive new information. The capabilities of explanation and debugging are also sometimes included in inference engines.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Expert system
Chapter 2: Learning classifier system
Chapter 3: AI winter
Chapter 4: Constraint logic programming
Chapter 5: Constraint satisfaction
Chapter 6: CLIPS
Chapter 7: Mycin
Chapter 8: Knowledge engineering
Chapter 9: Rule-based machine learning
Chapter 10: CADUCEUS (expert system)
(II) Answering the public top questions about expert system.
(III) Real world examples for the usage of expert system in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of expert system.
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