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This outline was last edited on 29 November 2007. Last edit over 120 months ago. Please update.
I do not know if I want to make this book either (a) a replacement for the existing Artificial Intelligence book, (b) A new book with a slightly modified title, or (c) a book focused on intellegent and expert systems. --Whiteknight (Page) (Talk) 02:35, 31 August 2007 (UTC)
- Target Audience
- Advanced undergraduate and graduate students in the fields of electrical engineering, computer engineering, computer science, or a related field.
- Will discuss intelligent systems, expert systems, A.I. and the current state of the art in these fields. Will not cover neural networks, genetic algorithms, or adaptive processes. Will discuss Prolog, Lisp, and related languages, but will not serve to teach them.
- Proficiency in computer programming (any language), solid understanding of computer systems and computer architectures. Formal Logic.
Table of Contents
- History of AI and Computing
- Intellegent Systems
Expert System Basics
- Introduction to Expert Systems
- Types of Expert Systems
- Components of Expert Systems
Tools and Shells
- What is Knowledge?
- Semantic Nets
- Propositional Logic
- Quantifiers and Sets
- The Agenda
- Forward Chaining
- Backward Chaining
- Rule Selection
- Deductive Reasoning
- Backward Induction
- Markov Chaining
- Dempster-Shafer Theory
- Fuzzy Logic
- Rete Algorithm
Expert System Examples
- Expert Tutoring Systems
- Turing, Allen, Computing Machinery and Intellegence, Mind, 1959, p433-460.
- Minsky, Marvin, Why People Think Computers Can't, AI Magazine, Vol 3 No 4, Fall 1982.
- Kurzweil, Ray, The Singularity is Near, Penguin Books, 2005. ISBN 0143037889
Initial outline based in part on:
- Giarratano, Joseph C., Riley, Gary D., Expert Systems: Principals and Programming, Fourth Edition, Thomson Course Technology, 2005. ISBN 0534384471
History of AI and Computing Intelligent Systems = Expert System Basics Introduction to Expert Systems Types of Expert Systems Components of Expert Systems = Tools and Shells Tools Shells Languages = Knowledge What is Knowledge? Productions Semantic Nets Frames Propositional Logic Quantifiers and Sets = Inference Engines Forward Chaining Backward Chaining Managing The Agenda = Uncertainty Dempster-Schaefer Probability Fuzzy Logic = Pattern Matching
+Reading level|Undergraduate &Logic &Computer Programming -Computer science -Computer engineering -Artificial intelligence History of AI and Computing Intellegent Systems = Expert System Basics Introduction to Expert Systems Types of Expert Systems Components of Expert Systems = Tools and Shells Tools Shells Languages CLIPS Jess Prolog = Knowledge What is Knowledge? Productions Semantic Nets Frames Propositional Logic Quantifiers and Sets = Inference Engines The Agenda Forward Chaining Backward Chaining Refraction Rule Selection Deductive Reasoning Resolution = Uncertainty Probability Backward Induction Markov Chaining Dempster-Shafer Theory Fuzzy Logic = Pattern Matching Rete Algorithm = Expert System Examples DENDRAL MYCIN PROSPECTOR Expert Tutoring Systems