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Expert Systems & Prolog
 

Expert Systems & Prolog

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Artificial Intelligence Course Slide

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    Expert Systems & Prolog Expert Systems & Prolog Presentation Transcript

    • THANK YOU ALL EXPERT SYSTEMS & PROLOG 1
    • EXPERT SYSTEMS OVERVIEW An experts system is a system that incorporates concepts derived from experts in a field and uses their knowledge to provide problem analysis through programs available to clinical practitioners. 2
    • EXPERT SYSTEMS IDEA OF EXPERT SYSTEMS The most common form of expert system is software made up of a set of rules that analyze information. 3
    • EXPERT SYSTEMS IDEA OF EXPERT SYSTEMS INPUT INPUT SYSTEM OUTPUT KNOWLEDGE KNOWLEDGE Result BASE Feedback BASE 4
    • EXPERT SYSTEMS SOME PROMINENT EXPERT SYSTEMS  Dendral, analyses mass spectra  CADUCEUS, blood-borne infectious bacteria  R1/XCon, order processing 5
    • EXPERT SYSTEMS SOME PROGRAMMING LANGUAGE Prolog, programming language used in the development of expert systems CLIPS, programming language used as Prolog to develop expert systems Jess (Java Expert System Shell), A CLIPS engine implemented in Java used to develop expert systems. 6
    • EXPERT SYSTEMS CHAINING There are two main methods of reasoning when using inference rules: Forward Chaining Backward Chaining 7
    • EXPERT SYSTEMS FORWARD CHAINING Forward chaining starts with the data available and uses the inference rules to conclude more data until a desired goal is reached. 8
    • EXPERT SYSTEMS FORWARD CHAINING An inference engine using forward chaining searches the inference rules until it finds one in which the if-clause is known to be true. It then concludes the then-clause and adds this information to its data. It would continue to do this until a goal is reached. 9
    • EXPERT SYSTEMS FORWARD CHAINING IF IF TRUE TRUE THEN THEN KNOWLEDGE ADD CONCLUDE BASE KNOWLEDGE D 10
    • EXPERT SYSTEMS BACKWARD CHAINING Backward chaining starts with a list of goals and works backwards to see if there is data which will allow to it to conclude ant of these goals. 11
    • EXPERT SYSTEMS BACKWARD CHAINING An inference engine using backward chaining would search the inference rules until it finds one which has a then-clause that matched a desired goal. 12
    • EXPERT SYSTEMS BACKWARD CHAINING Suppose a rule-based contains two rules: 1. If Fritz is green then Fritz is a frog. 2. If Fritz is a frog then Fritz hops. 13
    • EXPERT SYSTEMS BACKWARD CHAINING IF IF IF IF FRITZ is Green THEN THEN FRITZ is Frog THEN THEN Knowledge FRITZ is Frog Frog is green. Frog is green. Frog hops. Frog hops. 14
    • EXPERT SYSTEMS END USER Here is a dialog between end user and an expert system: 15
    • EXPERT SYSTEMS DIALOG: Q. Do you know which restaurant you want to go to? A. No Q. Is there any kind of food you would particularly like? A. No Q. Do you like spicy food? A. No Q. Do you usually drink wine with meals? A. Yes Q. When you drink wine, is it French wine? A. Yes 16
    • EXPERT SYSTEMS RESULT: A. I am trying to determine the type of restaurant to suggest. So far Chinese is not a likely choice. It is possible that French is a likely choice. I know that if the diner is a wine drinker, and the preferred wine is French, then there is strong evidence that the restaurant choice should include French. 17
    • PROLOG HISTORY The name Prolog was chosen by Philippe Roussel as an abbreviation for "PROgrammation en LOGique” (French for programming in logic). It was created around 1972 by Alain Colmerauerr with Philippe Roussell, based on Robert Kowalskis procedural interpretation of Horn clauses. 18
    • PROLOGDATA TYPESPrologs single data type is the term. Terms are either atoms,numbers, variables or compound terms. 19
    • PROLOGProgramming in Prolog Prolog programs describe relations, defined by means ofclauses. Pure Prolog is restricted to Horn clauses, a Turing-complete subset of first-order predicate logic. There are twotypes of clauses: Facts and rules. 20
    • PROLOGProgramming in Prolog An example of a fact is:cat(tom).which is equivalent to the rule:cat(tom) :- true. 21
    • PROLOGEVALUATIONExecution of a Prolog program is initiated by the usersposting of a single goal, called the query. Logically, theProlog engine tries to find a resolution refutation of thenegated query. The resolution method used by Prolog iscalled SLD resolution. If the negated query can be refuted, itfollows the query. 22
    • PROLOGFor example:sibling(X, Y) :- parent_child(Z, X), parent_child(Z, Y).parent_child(X, Y) :- father_child(X, Y).parent_child(X, Y) :- mother_child(X, Y). mother_child(trude,sally).father_child(tom, sally).father_child(tom, erica).father_child(mike, tom).This results in the following query being evaluated as true:?- sibling(sally, erica). Yes 23
    • PROLOG Related languages Visual Prolog, also formerly known as PDC Prolog and Turbo Prolog. Datalog is actually a subset of Prolog. In some ways Prolog is a subset of Planner. The ideas in Planner were later further developed in the Scientific Community Metaphor. 24
    • EXPERT SYSTEMS ADVANTAGES  Provide consistent answers for repetitive decisions, processes and tasks  Hold and maintain significant levels of information  Reduces creating entry barriers to competitors  Review transactions that human experts may overlook 25
    • EXPERT SYSTEMS DISADVANTAGES The lack of human common sense needed in some decision makings Domain experts not always being able to explain their logic and reasoning The lack of flexibility and ability to adapt to changing environments as questions are standard and cannot be changed Not being able to recognize when no answer is available 26