FIT3080: Intelligent Systems

Ramesh Kumar Ayyasamy

Sunway Campus

ramesh .kumar@monash.edu

My tutorial ground rules

1

During tutorial hours, you are allowed only to

- do the given tutorial tasks as mentioned in Moodle.

2

During tutorial hours, you are not allowed to

- not allowed to use Facebook, YouTube or any such activities which is not related to tutorial.

- not allowed to use mobile phones or chatting with your girl friends or boy friends.

- not to make loud noise.

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Today’s Tasks – Tutorial 5

Knowledge representation

1. Exercise 6: First Order Logic

2. Exercise 7: Equivalence

3. Exercise 8: Unification

4. Exercise 9, 10: Resolution refutation

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Knowledge representation with Logic

Limitation on propositional logic

•

Propositional logic can only handle TRUE, FALSE and has “No capability to handle

Uncertainty”, which is present in probability theory

•

It conveys only TRUE or FALSE of the world, but “does not considers objects that has properties such as size, weight, color, nor their relationships between objects”

•

No shortcuts or lacks expressiveness to describe the lots of activities happening around. •

First-order logic address the two limitations: objects and shortcuts

Refer, unit 7 in: https://www.ai-class.com/course/video/quizquestion/28

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Exercise 6: First-Order Logic

First-Order Logic (FOL) is expressive to represent a good deal of our common sense knowledge. Quantifiers used here are : (For all), x (there exists and x such that or For some x)

• Logical Operators used here are :

, , , ,

Example for First-order logic: “All kings are persons” can be written as

x King (x) Person (x) .

“For all x, if x is a king, then x is a person.”, where x is a variable.

Example for First-order logic: “ King John has a crown on his head” can be written as

x Crown (x) OnHead (x, John)

appears to be the natural connective