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

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

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.

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.

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

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

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

Meningitis diagnosis rules Culture :کشت

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

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

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

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

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

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

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.”

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

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

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

Meningitis prescription rules

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

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

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 ”

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.

Example Review Variable goal Rule priorities Accommodating user Numeric Relationships

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

Prescription change rules

Prescription change rules

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

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

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.

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

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.

Example 4: Automobile Diagnostics Expert System Blackboard:

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

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

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

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.

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

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

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

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.