Introduction to Artificial Intelligence - Old Questions

5.  Briefly describe the approaches of knowledge representation with example.

Knowledge representation (KR) is the study of how knowledge about the world can be represented and what kinds of reasoning can be done with that knowledge. Knowledge Representation is the method used to encode knowledge in Intelligent Systems.

Approaches to knowledge representation

•  Rule-based

        – IF <condition> THEN <conclusion>

•  Object-based

        – Frames

        – Scripts

        –Semantic Networks

        – Object-Attribute-Value(O-A-V Triplets)

•  Example-based : Case-based Reasoning (CBR)

Rule-based approach:

Rule-based systems are used as a way to store and manipulate knowledge to interpret information in a useful way. In this approach, idea is to use production rules, sometimes called IF-THEN rules. The syntax structure is

                IF <premise> THEN <action>

<premise> - is Boolean. The AND, and to a lesser degree OR and NOT, logical connectives are possible.

<action> - a series of statements

E.g. ―If the patient has stiff neck, high fever and an headache, check for Brain Meningitis‖. Then it can be represented in rule based approach as:

IF <FEVER, OVER, 39> AND <NECK, STIFF, YES> AND <HEAD, PAIN, YES> THEN add(<PATIENT,DIAGNOSE, MENINGITIS>)

Object based approach:

Frames: With this approach, knowledge may be represented in a data structure called a frame. A frame is a data structure containing typical knowledge about a concept or object. Each frame has a name and slots. Slots are the properties of the entity that has the name, and they have values or pointer to other frames.

E.g. 

Semantic Networks: Knowledge is represented as a collection of concepts, represented by nodes. Thus, semantic networks are constructed using nodes linked by directional lines called arcs. For e.g.

etc.