The inference process
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The Inference Process. Rules There are two main forms of Inferencing Forward Chaining Backward Chaining. The Inference Process. Rules Rules follow an IF…THEN format English IF the pump’s temperature is hot THEN follow maintenance instructions Aion DS

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The Inference Process

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The inference process

The Inference Process

  • Rules

  • There are two main forms of Inferencing

  • Forward Chaining

  • Backward Chaining


The inference process1

The Inference Process

  • Rules

  • Rules follow an IF…THEN format

  • English

    IF the pump’s temperature is hot

    THEN follow maintenance instructions

  • Aion DS

    IFMATCH pump with temperature is “hot”

    THEN

    send (print maintenance to pump)

    END


The inference process2

The Inference Process

  • MYCIN (an expert system to diagnose blood disorders)

  • IF

  • the site of the culture is Blood AND

  • the identity of the organism is Unknown AND

  • the strain of the organism is Gramneg AND

  • the morphology of the organism is Rod AND

  • the patient has been seriously burned

  • THEN

  • there is weakly suggestive evidence (0.4) that the

  • identity of the organism is Pseudomonas


The inference process3

The Inference Process

  • Forward vs. Backward Chaining

  • Do we drive the inference process based on the known facts (data) or on the questions (goals) we need answers to?

  • Data Driven

  • Starts with the known data and fires rules to infer new information(forward chaining)

  • Goal Driven

  • Starts with the goal and tries to match facts to the solution(backward chaining)


The inference process4

The Inference Process

  • Forward Chaining

    1Enter new data

    2Fire forward chaining rules

    3Rule actions infer new data values

    4Go to step 2

    5repeat until no new data can be inferred

    6If no solution, rule base is insufficient


The inference process5

The Inference Process

Forward Chaining

1

Add new data values to knowledge base

Get some new data

4

Fire forward chaining rules

2

Infer new data values from rule actions

3


The inference process6

The Inference Process

  • Cascading Rules

  • Only applicable in forward chaining

  • Rule executes causing inference of new data

  • New data is added to the knowledge base

  • New data added causes other rules to fire

  • Can be very time consuming and inefficient in large systems


The inference process7

The Inference Process

  • Forward Chaining

  • The data is usually entered “up front”

  • Is usually done on a form by form basis

  • Relevant questions must be grouped together

  • Rules will only fire when all information is available

  • The inference engine will not try to find out any unknown information

  • All possible questions need to be asked at the start of a consultation


The inference process8

The Inference Process

  • Why Forward Chain?

Reasons to Forward Chain

Examples

You want to know everything that can possibly be concluded about a set of data

Monitoring for mechanical problems on a production line

Scanning a new loan application for problem areas

Many conclusions are possible from a single data item

Filtering sensor data

It is important to communicate new conclusions to the user immediately

Advice to shut down faulty machines

Data entry errors


The inference process9

The Inference Process

  • Backward Chaining

    1State a specific goal (question)

    2Find rules which resolve the goal

    3At runtime, answer questions to satisfy the antecedents of the rules as required

    4Obtain a result (goal resolved or not)


The inference process10

The Inference Process

Backward Chaining

1

State primary goal to source

Source sub goals

Fire backward chaining rules

2

3

Primary goal sourced

4


The inference process11

The Inference Process

  • Why Backward Chain?

Reasons to Backward Chain

Examples

There is a clear set of statements which must be confirmed or denied

Which machine is causing the quality control problem?

A large number of questions could be asked of the user, but typically only a few are necessary to resolve a situation

Processing of a motor claim for vandalism; not necessary to know about personal injuries

It is desirable to have interactive dialogue with the user

Asking machine operator detailed questions about suspect machinery

Rule execution depends on data gathering which may be expensive or difficult

Real-time observations by the user


The inference process12

The Inference Process

  • Backward or Forward Chaining?

  • Criteria to consider -

  • The logical reasoning process

  • Design features of the system

  • What are the inputs and where do they come from?

  • What are the outputs and where do they go?

  • How do these map to forward or backward chaining?


The inference process13

The Inference Process

  • Examples

Use Forward Chaining

Use Backward Chaining

Sensor indicates machine failure; want to find out what happens next

Defect observed in product; want to locate faulty machine

User types erroneous input for insurance claim; want to alert user

Suspect an overpayment; want to check form for erroneous input

Stock value suddenly drops; want to predict market response

FTSE industrials drop; want to know which stocks will be affected


The inference process14

The Inference Process

  • Chaining in Action

  • A list of known facts -A, B, D, G, P, Q, R, S.


The inference process15

The Inference Process

  • Chaining in Action

  • A list of known facts -A, B, D, G, P, Q, R, S.

Raining outside?


The inference process16

The Inference Process

  • Chaining in Action

  • A list of known facts -A, B, D, G, P, Q, R, S.

Cold?


The inference process17

The Inference Process

  • Chaining in - X is the goal

  • A list of Rules

    1A + I => X

    2A+B => C

    3C+D => E

    4F+G => H

    5E+H => X

    6A+C => F

    7P+Q => R

    8R+S => T


The inference process18

The Inference Process

  • Chaining in Action (Backward)

  • A list of Rules

    1A + I => X

    2A+B => C

    3C+D => E

    4F+G => H

    5E+H => X

    6A+C => F

    7P+Q => R

    8R+S => T

Rule 1 never fired because either “I” was not true or the user did not know it was true

Rules 7+8 never fired because they were not relevant to proving our goal of “X”, though they may have been used if we had another consultation with a different goal


The inference process19

The Inference Process

  • Chaining in Action (Forward)

  • A list of known facts -“A, B, D, P, Q, R, S”, are all true (we asked the user) and “I” is false or not known


The inference process20

The Inference Process

  • Chaining in Action (Forward)

  • A list of Rules

    1A + I => X

    2A+B => C

    3C+D => E

    4F+G => H

    5E+H => X

    6A+C => F

    7P+Q => R

    8R+S => T


The inference process21

The Inference Process

  • Chaining in Action (Forward)

  • A list of Rules

    1A + I => X

    2XA+B => C

    3XC+D => E

    4F+G => H

    5E+H => X

    6XA+C => F

    7XP+Q => R

    8XR+S => T


The inference process22

The Inference Process

  • Backward or Forward Chaining?

  • Backward chaining was more focused but only answered the question asked

  • Forward chaining found all possible results but needed more information “up front”

  • Backward chaining never used rules 7 and 8


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