PPT-EXPERT SYSTEMS Review – Classical Expert Systems

Can incorporate Neural Genetic and Fuzzy Components Expert Systems can perform many functions Rules can be fuzzy quantum modal neural Bayesian etc Special inference methods may be used Concepts of Knowledge Representation . Even though we are familiar with several pr oblemsolving techniques in the real world sometimes many problems cannot be solved by a technique we are familiar with Surprisingly for some compli cated problems no straight forward solution technique is However since most of these expert systems are based on text analysis rather than on models of hum man searching they cannot process requestrelated cri teria such as precision or recall requirements Analysis of the searching behavior of human interm . . . . By James Jennings. Introduction. . What is an Expert system?. expert system. is a computer system that emulates the decision-making ability of a human . expert. . Four . interactive roles form the activities of the expert system: . Eddie Lai. History. 1950s – scientists tried to use computers for “probabilistic reasoning and statistical pattern recognition”. 1970s – realized that physicians do not make decisions based on probability or patterns. SESSION 1. Introduction to Knowledge-based Intelligent Systems. By: . H.Nematzadeh. What is intelligence?. Intelligence is the ability to think and understand instead of doing things by instinct or automatically. (Essential English Dictionary, Collins, London, 1990). California State University, Northridge. Victoria . Chiu. SUNY New . Paltz.  . Qi . Liu and Pei Li. Rutgers University, The State University of New . Jersey. University of . Waterloo Symposium on . Information . By: . H.Nematzadeh. ASSESSMENT. Midterm Exam = 8/20. Final Exam = 10/20. Research Paper = 2/20. - 20 minutes presentation of the selected . paper . (WORLDCOMP’10:. USA. , IEEE’11: . . IE 469 Manufacturing Systems. 4. 69. . صنع . نظم . التصنيع. Outline. Introduction to Expert Systems (ES). Components of an ES. Building an ES. Implementations/References. 2. Introduction. Leroy Garcia. 1. Definition of AI. Artificial Intelligence is . the branch of computer science that is concerned with the automation of intelligent behavior. (Luger, 2008). . 2. Different Approaches to AI. Can incorporate Neural, Genetic and Fuzzy Components. Many expert systems are based on rules. Expert Systems can perform many functions. Rules can be fuzzy, quantum, modal, neural, Bayesian, etc.. Special inference methods may be used. I DT LO rELE CTE -i EC 2 11 33t-fCq -u nUCir aol0 N L- - DEPARTMENT OF THEi AIR FORCEAIR UNWIERSITYAIR FORCE INSTITUTE OF YECI-MOLOGYWrighi-Patterson Air Force Base OhioAFIT/GEM/LSM/88S-9OTICSELE III YEAR VI. SEM. Presented by,. . Ms. M. . Rupa. , . AP/CSE,JCTCET. Motivation & Objectives. Utilization of computers to deal with knowledge. Quantity of knowledge increases rapidly. Knowledge might get lost if not captures.