Lecture 6 - Knowledge and Expert Systems Flashcards

1
Q

Pre-1970s is known as the _________ Era

A

Heuristic Search Era

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2
Q

In the Heuristic Search Era, the quest for the essence of intelligence focused on two areas:

A

Universal Problem Solving Techniques

Universal Learning Techniques

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3
Q

Search techniques and General Problem Solving are both part of

A

Universal Problem Solving Techniques

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4
Q

Perceptrons are part of

A

Universal Learning Techniques

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5
Q

Both universal problem solving techniques and universal learning techniques are characterised by

A

Absence of a priori knowledge of the problem domain (i.e. no knowledge or understanding before the problem solving begins)

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6
Q

Post 1970s is known as the

A

Knowledge Based Systems Era

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7
Q

The Knowledge based systems era is characterised by

A

Recognition of central role of knowledge in all types of intelligent activity

Shift of research emphasis to study of techniques for representing and using knowledge

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8
Q

What was Dendral?

A

The first serious attempt to produce a system as good as a human expert in a real world problem domain

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9
Q

In what years was Dendral under devleopment?

A

1965-1972

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10
Q

What was Dendral’s task?

A

Determine structure of a chemical compound from mass spectrogram data

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11
Q

How does a mass spectrogram work?

A

Smash up molecules

Get a histogram of fragment masses

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12
Q

What knowledge did dendral have?

A

Chemical formula of the compound

Atomic weights of chemicals and compounds

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13
Q

Why was Dendral’s task particularly difficult?

A

Huge search space -

Atoms may be joined in many different configurations

Organic compound with only 20 atoms can have up to 104 isomers

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14
Q

What would be the naive solution to Dendral’s task, and why is it a stupid idea to use this?

A

Generate all possible structures of the compound

For each, check if it is consistent with spectral data

Not used because it is very computationally expensive

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15
Q

What solution did dendral use for its task?

A

Use knowledge about the problem domain to constrain generation of candidate solutions

e.g. substructures the molecule is known to contain

substructures the molecule is known not to contain

which bonds are more likely to break

Far fewer candidates generated this way!

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16
Q

What is the 8 Queens problem?

A

Illustration how the use of additional knowledge can reduce number of candidates in generate and test procedure:

place 8 queens on an 8x8 chessboard so no queen occupies a square attacked by any of the others

17
Q

What is the naive 8 queens solution?

A

Generate all possible configurations of 8 queens on a board

For each, check if it satisfies the conditions

18
Q

How many possible configurations of 8 queens are on a 8x8 chessboard?

A

64*63*62*61*60*59*58*57=2x104

Checking a million configs a second would take 5.6 years to execute

19
Q

What constraint can be added to the 8 queens problem to reduce the number of configurations?

A

Only allow one queen in each row

no. solutions = 88=2x107

Execution time reduced to ~20 seconds

20
Q

What lessons can we learn from Dendral?

A

Searching is easy but time consuming

Intelligence lies in constraining the search to reduce time

Adding constraints is harder than programming a basic search

Constraints embody domain specific knowledge

21
Q

From Dendral we learn we need to replace this with

A

this

22
Q

What is a Production System?

A

A set of production rules

23
Q

What is a production rule?

A

Codify knowledge as a set of states and actions, e.g.

IF IT IS RAINING THEN PUT UP YOUR UMBRELLA

situation action

24
Q

Production rules are essentially

A

Ordered pairs

25
Q

The state component of a production rule is often called

A

condition

antecedent

left hand side or LHS

26
Q

The action component of a production rule is often called

A

Consequent

Right hand side or RHS

27
Q

What are the advantages of production systems?

A

Easy to program - if … then very basic construct

Modular - each bit of knowledge has its own rule - easy to add or remove rules

Easy to show user how the result was reached

Reaches decisions in a very natural fashion