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     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 Kowalski's procedural
    interpretation of Horn clauses.


                                                               18
PROLOG

DATA TYPES

Prolog's single data type is the term. Terms are either atoms,
numbers, variables or compound terms.




                                                             19
PROLOG

Programming in Prolog


 Prolog programs describe relations, defined by means of
clauses. Pure Prolog is restricted to Horn clauses, a Turing-
complete subset of first-order predicate logic. There are two
types of clauses: Facts and rules.




                                                                20
PROLOG

Programming in Prolog


 An example of a fact is:

cat(tom).



which is equivalent to the rule:

cat(tom) :- true.



                                   21
PROLOG

EVALUATION


Execution of a Prolog program is initiated by the user's
posting of a single goal, called the query. Logically, the
Prolog engine tries to find a resolution refutation of the
negated query. The resolution method used by Prolog is
called SLD resolution. If the negated query can be refuted, it
follows the query.


                                                                 22
PROLOG
For 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

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Expert Systems & Prolog

  • 1. THANK YOU ALL EXPERT SYSTEMS & PROLOG 1
  • 2. 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
  • 3. 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
  • 4. EXPERT SYSTEMS IDEA OF EXPERT SYSTEMS INPUT INPUT SYSTEM OUTPUT KNOWLEDGE KNOWLEDGE Result BASE Feedback BASE 4
  • 5. EXPERT SYSTEMS SOME PROMINENT EXPERT SYSTEMS  Dendral, analyses mass spectra  CADUCEUS, blood-borne infectious bacteria  R1/XCon, order processing 5
  • 6. 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
  • 7. EXPERT SYSTEMS CHAINING There are two main methods of reasoning when using inference rules: Forward Chaining Backward Chaining 7
  • 8. 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
  • 9. 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
  • 10. EXPERT SYSTEMS FORWARD CHAINING IF IF TRUE TRUE THEN THEN KNOWLEDGE ADD CONCLUDE BASE KNOWLEDGE D 10
  • 11. 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
  • 12. 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
  • 13. 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
  • 14. 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
  • 15. EXPERT SYSTEMS END USER Here is a dialog between end user and an expert system: 15
  • 16. 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
  • 17. 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
  • 18. 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 Kowalski's procedural interpretation of Horn clauses. 18
  • 19. PROLOG DATA TYPES Prolog's single data type is the term. Terms are either atoms, numbers, variables or compound terms. 19
  • 20. PROLOG Programming in Prolog Prolog programs describe relations, defined by means of clauses. Pure Prolog is restricted to Horn clauses, a Turing- complete subset of first-order predicate logic. There are two types of clauses: Facts and rules. 20
  • 21. PROLOG Programming in Prolog An example of a fact is: cat(tom). which is equivalent to the rule: cat(tom) :- true. 21
  • 22. PROLOG EVALUATION Execution of a Prolog program is initiated by the user's posting of a single goal, called the query. Logically, the Prolog engine tries to find a resolution refutation of the negated query. The resolution method used by Prolog is called SLD resolution. If the negated query can be refuted, it follows the query. 22
  • 23. PROLOG For 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
  • 24. 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
  • 25. 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
  • 26. 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