Rules: Knowledge Representation

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RulesKnowledge Representation Manipulation

• Artificial Intelligence
• CMSC 25000
• January 8, 2002

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Agenda

• Knowledge Representation
• Assertions Rules
• Knowledge Manipulation
• Forward Backward Chaining
• Deduction Reaction Systems
• Costs, Choices, and Mechanisms

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Representing Knowledge

• Assertion
• Statement that something is true
• Stretch is a giraffe,The sky is blue
• Collection of assertions Working Memory

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Representing Knowledge Rules

• If - then rules

If A1, A2
Antecedent
Then B1, B2
Consequent
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Representing Knowledge Rules

• May include variables, e.g.
• Variables ?x,?y,?z
• Same name gt same value

If (parent-of ?x ?y), (parent-of ?y
?z), then (grandparent-of ?x ?z)
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Knowledge Manipulation

• Forward chaining
• Reason from if antecedents to then
  consequents
• Backward chaining
• Confirm hypothesis matching then patterns by
  verifying if patterns

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Rule-based Systems

• Separate knowledge from control
• Contrast from typical programming Integrated

Add consequent
Assertions
Rules
Rule Interpreter
Select rule
Match antecedent
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Forward Chaining

• Identify triggered rules
• Antecedents match assertions
• Match variables -gt rule instances
• Select a triggered rule to fire
• Conflict resolution strategy first, random, LRU,
  combination
• Fire a rule
• Add consequents to list of assertions (deduction)
• Perform action(s) in consequent (reaction)

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Forward Chaining Example
R1 if (signs (nasal congestion)) (signs
(viremia)) then (diagnosis influenza) R2
if (runny nose) then (signs (nasal
congestion)) R3 if (body-aches) then
(signs (achiness))
R4 if (temp gt100) then (signs
(fever)) R5 if (headache) then (signs
(achiness)) R6 if (signs (fever))
(signs (achiness)) (cough) then
(signs (viremia))
Assertions F1 runny nose F2 temp 101.5 F3
headache
Execution
R2 Fires Asserts (signs (nasal congestion)) R4
Fires Asserts (signs (fever)) R5 Fires Asserts
(signs (achiness)) R6 Fires Asserts (signs
(viremia)) R1 Fires Asserts (diagnosis
influenza)
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Forward Chaining with variables
IF (parent ?x ?y) (parent A B)
(parent ?y ?z) (parent A C) THEN
(grand-parent ?x ?z) (parent B D)
(parent C E)

• (parent ?x ?y) (parent ?y ?z) (grand-parent ?x
  ?z)
• (xA yB) (yA zB) conflict in y
• (yA zC) conflict in y
• (yB zD) (xA yB zD)
• (yC zE) conflict in y
• (xA yC) (yA zB) conflict in y
• (yA zC) conflict in y
• (yB zD) conflict in y
• (yC zE) (xA yC zE)
• (xB yD) (yA zB) conflict in y
• (yA zC) conflict in y
• (yB zD) conflict in y
• (yC zE) conflict in y
• (xC yE) (yA zB) conflict in y

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Forward Chaining Analysis

• Reason from antecedents to consequents
• Trigger rules if all antecedents match assertions
• Add assertions or do actions in consequents
• May be computationally expensive
• Many possible deductions to make
• Brute force approach k antecedents, N assertions
• Nk!!
• Rete method

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Backward Chaining

• Test hypothesis
• Reason from consequents to antecedents
• Use assertions and rules
• If no assertions or rules give evidence, ask
  questions

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Backchain(G) - Rule interpreter

• If G matched assertion in database, then return
  True
• Else
• If there are rules whose consequent matches G
• For each matching rule R
• For each antecedent C of R
• If Backchain(C) is true, proceed
• Else go to next rule.
• Return True / when all antecedents are true /
• Return False / when no matching rule succeeds /
• Else, ask user if G is true.
• If answer is yes return True,
• Else return False.

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Backward Chaining Example
R1 if (signs (nasal congestion)) (signs
(viremia)) then (diagnosis influenza) R2
if (runny nose) then (signs (nasal
congestion)) R3 if (body-aches) then
(signs (achiness))
R4 if (temp gt100) then (signs
(fever)) R5 if (headache) then (signs
(achiness)) R6 if (signs (fever))
(signs (achiness)) (cough) then
(signs (viremia))
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Backward Chaining Example
Hypothesis (diagnosis influenza)
Diagnosis Influenza
AND
(Signs (nasal congestion))
(Signs (viremia)
AND
(Runny nose)
(Signs (fever))
(Signs (achiness))
(cough)
Ask
Ask
OR
Yes
Yes
(Temp gt 100)
Ask
Yes
(Body-ache)
(Headache)
Ask
Ask
No
Yes
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Reaction Systems

• Deduction systems
• Produce new assertions
• Keep firing all triggered rules
• Order less important
• Reaction systems
• Produce arbitrary actions assertions, printing,
  moving, bagging
• Side effects -gt Order important

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Reaction System Example

• For example,
• IF (at ?x ?y)
• (move ?x to ?z)
• ADD (at ?x ?z)
• DELETE (move ?x to ?z)
• (at ?x ?y)
• Assume an initial database
• (at A room1) (move A room2)
• Then the rule would add (at A room2)
• And, delete
• (at A room1) (move A room2)

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Conflict Resolution

• When gt1 rule is triggered, which fires??
• First Rules are ordered. Fire first triggered.
• Random Randomly select a rule to fire
• Most specific Fire rule with most antecedents
• Least recently fired Avoids rule starvation.
• Combination
• Design rule set wrt conflict resolution strategy

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Conflict Resolution Deduction

• Generally, less important,but
• Possible to create infinitely recursive rule
• if ?x, (not (not ?x)).
• Need conflict resolution
• Allow other rules to fire
• E.g. stop rule