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IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI)

IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI). Tutorial KBS in Business (a video) Example for Backward Chaining. KBS in Business (a video). We will be watching a video on “ Expert systems for business benefit” We will be discussing the following issues before and after the video

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IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI)

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  1. IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI) • Tutorial • KBS in Business (a video) • Example for Backward Chaining

  2. KBS in Business (a video) • We will be watching a video on “Expert systems for business benefit” • We will be discussing the following issues before and after the video • Where the KBS/ES has been used • What benefits have been mentioned • If any difficulties or disadvantages are discussed? If you wish, you can borrow the video from the main library: Expert systems for business benefit [Videorecording], Video 006.33/EXP In addition, you may look at the followings: 1. Expert systems [Videorecording] : techniques and applications. - Video 1 : The automation of expertise / Jim Alty, Video L 006.33/ALT 2. Expert systems [videorecording] : automating knowledge acquisition / by Donald Michie and Ivan Bratko, Video 006.33/MIC 3. Professional judgment [Videorecording]: Knowledge based systems, Video WD321\4

  3. Tutorial: Forward & Backward Chaining Suppose the following rules and facts are given: Rule 1: if A and B and C then D Rule 2: if A and E then C Rule 3: if B and C then A Rule 4: if C and E then B Fact 1: E is true Fact 2: A is true 1. With reference to the above example rules and facts, show how D can be proved true by backward chaining 2. Suppose the truth-value of E is unknown during a backward chaining inference process. The system may ask the user for its value. Explain briefly the response of this expert system if the user asks the question ‘why is the truth-value of E required?’

  4. Answer 2 In backward chaining the system has a goal stack and a record of the rules applied. This can be used to tell the user why he/she us being asked for a truth-value. In this case, the response would be ‘because I am trying to prove that C is true using Rule 2 ‘if A and E then C’ and I know that ‘A is true’ (Fact 2). Answer 1 Goal: D Truth-value of D unknown Only one rule has D as a conclusion – Rule 1 Set up sub-goals A and B and C (antecedents) to replace D – goals are A,B,C Now goal is A Fact 2 is A is true Unstuck goal – new goal is B – goals are B, C New goal is B B truth-value is not known Only 1 rule has B as a conclusion - Rule 4 Set up sub-goals C and E (antecedents) – goals are C, E, C New goal is C C truth-value is unknown Only 1 rule has C as a conclusion – Rule 2 Set up sub-goals A and E (antecedents) – goals are A, E,E,C New goal is A Fact 1: A is true – un-stack A – goals are E, E, C New goals is E Fact 2 E is true – un-stack E – goals are E, C New goal is E Fact 2: E is true – un-stack E – goals are C C truth values is unknown Only one rule has C as a conclusion – Rule 2 Set up sub-goals A and E – goals are A, E New goal is A Fact 1 A is true – un-stack – goals are E New goal is E Fact 2 E is true – un-stack – goal is null Hence proved D is true.

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