Knowledge Representation

Question 1

What are the three aspects of knowledge reasoning?

Answer 1

1. Syntactic - possible (allowed) constructions, each individual representation is called a sentence, e.g. colour(my_car, red)
2. Semantic - what does the representation mean? Maps sentences to the world
3. Inferential - the interpreter, decides what kind of conclusions can be drawn

Question 2

Name 3 types of logic other than first-order and simple.

Answer 2

1. 3-valued (true, false, unknown)
2. Fuzzy - degree of membership [0,1] - imprecision
3. Bayesian - degree of confidence [0,1] - belief

Question 3

Name some pros and cons of using logic.

Answer 3

Pros:

• Easy to translate
• Well-studied
• Language representation such as Prolog

Cons:

• Can be difficult if you don’t know logic
• Not a natural representation

Question 4

What are the KR (Knowledge Representation) language requirements?

Answer 4

Representation adequacy
- should allow representing all the required knowledge

Inferential adequacy
- should allow inferring new knowledge

Inferential efficiency
- inferences should be efficient

Clear syntax and semantics
- unambiguous and well -defined syntax and semantics

Naturalness
- easy to read and use

Question 5

What are the production rules?

Answer 5

Rule set of pairs:
- “If condition then action”

Match-resolve-act cycle:

• Match: agent checks if each rule’s condition holds
• Resolve:
• • Multiple production rules may fire at once (conflict set)
• • Agent must choose role from set (conflict resolution)
• Act: if so, rule “fires” and the action is carried out

Working memory:

• Rule can write knowledge to working memory
• Knowledge may match and free other rules