1. Backward-Chaining Rule-Based Systems
Provided: Sharif Students
Modified: Vali Derhami

2. Chapter 7 overview: Introduction Medical consultation systems
Example 1:Meningitis Diagnosis Expert System
Example 2:Meningitis Prescription Expert System
Example 3:Alternative Prescription Expert System
Automobile Diagnostic System
Example 4:Automobile Diagnostic via a Blackboard
Summary

3. Introduction
The principle objective of backward chaining is to prove some goal or hypothesis
The process begins by collecting GOAL RULES
Goal Rules contain the goal proven in their THEN part
The premise of the goal rules may be supported by other rules, so they are set as Sub-Goals
The inference engine searches through the system’s rules in a recursive fashion.

4. Backward Chaining inference engine will reach some premise that is not supported by any of the system’s rules (a Primitive)  Ask User
The answer is placed in the current memory
The process continue until all goals and sub-goals are searched  memory contains all information provided by user and inferred by rules.

5. Medical Consultation Systems
Like MYCIN , performs diagnosis for infectious blood diseases
Unlike MYCIN , doesn’t identify organ but rather the nature of the infection
3 different expert systems: Diagnosis(تشخیص), Prescription (تجویز), Prescription Changes

6. Design Suggestion
Divide Complex problems into smaller tasks and design system for each task.

7. Example 1: Megningitis Diagnosis Expert System
The system has only one goal :
Prove or disprove “Infection (عفونت یا مرض)is meningitis”
One Goal rule : RULE 1
This can be proven if the user already knows that the patient has meningitis or the system can infer it.
RULE 2,3,4 : search the test results
RULE 5 : searches the area of patient symptoms

8. Meningitis diagnosis rules
Culture :کشت

9. Medical Diagnosis Example Session
Begins with empty working memory
STEP 1: Find rules with hypothesis in “THEN” part
RULE 1
STEP 2: see if first premise in RULE 1 is listed in working memory NO
STEP 3: see if this premise exists in “THEN” part of any rule

10. STEP 4: This premise is a primitive
Question : “Do you know if patient has Meningitis ?”
Answer : NO
Working Memory: Patient known to have Meningitis - FALSE
STEP 5: look at second premise in RULE 1 and see if it’s in working memory NO
STEP 6: see if this premise exists in “THEN” part of any rule
RULE 2
نحوه تولید سوال: خود سیستم سوال را تولید کند
هر مقدمی که میخواهد سوال شود قبلا سوالش اضافه شده باشد

11. STEP 7: see if first premise in RULE 2 is listed in working memory NO
STEP 8: see if this premise exists in “THEN” part of any rule
RULE 3
STEP 9: Q: Were test run?
USER: YES
STEP 10: Q: Were cultures seen?
USER:YES
STEP 11: Q: The appearance of the culture is coccus?
USER: WHY
System: This will aid in determining if cultures look like Meningitis
نحوه تولید سوال: خود سیستم سوال را تولید کند
هر مقدمی که میخواهد سوال شود قبلا سوالش اضافه شده باشد

12. STEP 11: Q: The appearance of the culture is coccus (نوعی باکتری )?
USER: WHY
System: This will aid in determining if cultures look like meningitis
RULE 4
STEP 12: USER : WHY 4.0
System: This will determining if “we suspect meningitis from test results”
RULE 3
STEP 13:
System: The appearance of the culture is coccus?
USER: NO

13. Working Memory Tests Run-TRUE Cultures Seen-TRUE
Patient known to have meningitis-FALSE
Tests Run-TRUE
Cultures Seen-TRUE
Appearance of cultures is coccus-FALSE
The system was unsuccessful in establishing meningitis from test results

14. STEP 15: see if this premise exists in “THEN” part of any rule
STEP 14: look at second premise in RULE 2 and see if it’s in working memory NO
STEP 15: see if this premise exists in “THEN” part of any rule
RULE 5
STEP 16: All premises of RULE 5 are unknown and primitives Questions
SYSTEM: Has the patient been suffering persistent headaches (سردرد)?
USER: YES

15. STEP 17: RULE 5 fires RULE 2 fires RULE 1(Goal Rule) fires
SYSTEM: Has the patient been suffering dizziness(سرگیجه)?
USER: YES
SYSTEM: Has the patient been lethargic(بی حس و حال)?
STEP 17: RULE 5 fires RULE 2 fires RULE 1(Goal Rule) fires
SYSTEM: “After considering your info, I believe the infection is Menningitis.”

16. Example Review Simple Goal Simple Questions Depth First Search
Intelligent User
Safety Net: Using “Display” command
نمایش نتایج میانی
Ease of Expansion
Documenting of Rules
Inference Network

17. Inference network
Graphical representation of the systems’ rules with the premises and conclusions of the rules drawn as nodes and their supporting relationships drawn as links

19. Example 2: Meningitis Prescription Expert System
Prescription task: formulate action needed to correct the fault
Problem Solving Approach :
- The rules are shown in next slide.
- We have one goal to prove :
“Prescription is ? Prescription”
2 goal rules : RULES 1 ( higher priority ) and 2
RULE 3 : patient’s age

20. Meningitis prescription rules

21. Medical Prescription Example Session
The fact that patient has meningitis is known
GOAL : )Prescription is ? )Determine proper series of drugs
STEP 1: Find rules with hypothesis in “THEN” part
RULE 1 and RULE 2
STEP 2: chose RULE 1 because of higher priority and see if first premise in RULE 1 is listed in working memory
YES
STEP 3: see if the second premise of RULE 1 exists in working memory NO

22. STEP 4: see if this premise exists in “THEN” part of any rule
STEP 5: see if this premise of RULE 3 is listed in working memory NO
STEP 6: see if this premise exists in “THEN” part of any rule

23. STEP 7: This premise is a primitive
Question : “What is the patient’s age?”
Answer : 8
STEP 8: Rule 3 fires (patient is a child)  Rule 1 also fires
SYSTEM : “My first recommendation is this :
Ampicillin --- Dose : 3.8 g
Gentamicin --- Dose : 131 mg ”

24. STEP 9:
USER: HOW
SYSTEM : To drive goal ”Prescription is ? Prescription” I considered:
-RULE1(1.1 is known to be true)
-To drive 1.2 I considered RULE3
-To drive 3.1 I asked you. your answer was 8.
-RULE 3 was concluded.
-RULE 1 was concluded.

25. Example Review Variable goal Rule priorities Accommodating user
Numeric Relationships

26. Example 3: Alternative Prescription Expert System
Non-Monotonic Reasoning : facts that are logically dependent on other facts that have been retracted can be retracted.
Retract ()
Logical ()
Database Access:
- Using existing knowledge
- Using general knowledge

27. Prescription change rules

28. Prescription change rules

29. Prescription change functions
Display current drugs
Determine deleted drugs
Determine substituted drugs
Determine if drug is effective
Determine if drug is safe
Compare ages
Try another drug: Using “CYCLE” command
Remember facts
Recycle

30. Alternative Prescription Example Session
Drug recommendation AMPICILIN-TRUE
Drug recommendation GENTAMICIN-TRUE
GOAL: allow user choose alternative drug
SYSTEM: do you want to consider another prescription?
USER: YES
SYSTEM: which one do you want to delete?
USER: ampicilin
SYSTEM: what drug do you want to add?
USER: stremptomycin

31. SYSTEM: The requested drug comes from class AMINOGLYCOSIDES and would not be effective. you could try another drug.
USER: PENICILIN
SYSTEM: The requested drug comes from class PENNICILLINS and would be an effective replacement for AMPICILLIN which also comes from PENNICILLINS.

32. Example Review Ease of modification General knowledge
Monotonic Reasoning
Non-Monotonic Reasoning

33. Automobile Diagnosis System
Design Suggestion: For problems that require expertise from more than one individual, develop separate expert systems that capture the expertise of each individual.
Blackboard: The mean for information exchange when the ES is designed to incorporate separate expert modules.

34. Example 4: Automobile Diagnostics Expert System
Blackboard:

36. Example 4: Automobile Diagnostics Expert System
Object Attribute Value: allows you to display to user a menu of possible values.

37. Automobile Diagnostics Example Session
SYSTEM: please tell me whether the engine WILL START,WON’T START?
USER: won’t start
SYSTEM: please tell me whether the starter DOES TURN,DOESN’T TURN?
USER: does turn
SYSTEM: the engine turns VERY SLOWLY, NORMALLY BUT WON’T START?
USER: normally but won’t start

38. SYSTEM: I believe the problem might be with the FUEL SYSTEM
SYSTEM: I believe the problem might be with the FUEL SYSTEM. I will check with my expert in this area.
SYSTEM: The fuel gage DOESN’T MOVE,DOES MOVE?
USER: does move
SYSTEM: The car will START OCCASIONALLY, NEVER STARTS?
USER: star occasionally

39. SYSTEM: After working on your problem it is my belief that your car has problem with the FUEL SYSTEM.
The specific problem is DIRTY CARBURETOR.
My recommendation is REBUILD THE CARBURETOR.
The cost for such repair is 100 dollars.

40. Example Review Separate Systems Meta Rules
Display of intermediate findings
Blackboard
O-A-V facts
Initializing knowledge: INIT , REINIT
Intelligent Safety Net
Reinit , init
در بعضی از پوسته های یکسان هستند ولی بعضا reinit وقتی عمل میکند که سیستم د رابتدا با دستور chain فراخوانی میشود

41. Summary on Backward Chaining Expert Systems
BC attempts to prove a goal by recursively moving back through the rules in search of supporting evidence
To ease the development and maintenance of these systems, design them in modular form
Care should be given to provide clear final displays and keeping user informed

42. The user should allow user to provide known information and avoid unnecessary search by the system
Some intelligent findings should be provided even if the system is not totally successful
Database information should be used
Cooperating expert systems modules communicate over a structure known as Blackboard

43. تمرين: 3 نمونه از كاربردهاي سيستم هاي خبره كه در مقالات يا گزارشات علمي آمده است را با توضيح در حدود 10 خط براي هر مورد بيان كنيد.