1. Artificial Intelligence
Lecture 3
Artificial Intelligence
Fahad
CS&IT, Lahore Leads University 1

2. Knowledge Representation1

3. Overview Knowledge Processing
Motivation
Objectives
AI Life Cycle
Knowledge Types 3

4. Knowledge Representation
A subarea of Artificial Intelligence concerned with understanding, designing,
and implementing ways of representing information in computers so that programs (agents) can use this information •
to derive information that is implied by it,
to converse with people in natural languages,.

5. to decide what to do next
to plan future activities,
to solve problems in areas that normally require human expertise

6. Catching My Plane
Scenario for an examination of knowledge representation and reasoning:
A traveller wants to know when he/she needs to leave his/her hotel in order to catch a plane
background knowledge
situation knowledge
acquisition of additional knowledge for decision making
reasoning methods
verification and validation

7. Computer Scenario
Traveler posts a query to a computer

8. Google:

9. Bing:

10. Ask.com:

11. Human Scenario
Traveler asks a human
e.g. hotel receptionist

12. Motivation
Representation and manipulation of knowledge has been essential for the development of humanity as we know it
Use of formal methods and support from machines can improve our knowledge representation and reasoning abilities
Intelligent reasoning is a very complex phenomenon, and may have to be described in a variety of ways
Basic understanding of knowledge representation and reasoning is important for the organization and management of knowledge

13. Objectives
be familiar with the commonly used knowledge representation and reasoning methods
examine the suitability of knowledge representations for specific tasks
evaluate the representation methods and reasoning mechanisms employed in computer-based systems

14. The AI Cycle
Almost all AI systems have the following components in general:
Perception
Learning
Knowledge Representation and Reasoning
Planning
Execution
the process of using the senses to acquire information about the surrounding environment or situation

15. The AI Cycle

16. Knowledge and its types
what the ‘knowledge’ is?
Durkin refers to it as the “Understanding of a subject area”.
A well-focused subject area is referred to as a knowledge domain, for example, medical domain, engineering domain, business domain, etc..

17. Knowledge and its types
If we analyze the various types of knowledge we use in every day life, we can broadly define knowledge to be one of the following categories:

18. Knowledge Representation
Types of Knowledge
Factual
Subjective
Heuristic
Deep or Shallow
Other Types

19. Factual Knowledge Verifiable
through experiments, formal methods, sometimes commonsense reasoning
often created by authoritative sources
typically not under dispute in the domain community
often incorporated into reference works, textbooks, domain standards

20. Subjective Knowledge Relies on individuals
insight, experience
possibly subject to interpretation
more difficult to verify
especially if the individuals possessing the knowledge are not cooperative
different from belief
both are subjective, but beliefs are not verifiable

21. Heuristic Knowledge
Based on rules or guidelines that frequently help solving problems
often derived from practical experience working in a domain
as opposed to theoretical insights gained from deep thoughts about a topic
verifiable through experiments
Graphs and games like Tic Tac Toe

22. Deep and Shallow Knowledge
deep knowledge enables explanations and credibility considerations
possibly including formal proofs
shallow knowledge may be sufficient to answer immediate questions, but not for explanations
heuristics are often an example of shallow knowledge
Shallow is for time-being consideration while deep is long-term

23. Other Types of Knowledge
Procedural knowledge
Describes how to do things, provides a set of directions of how to perform certain tasks, e.g., how to drive a car.
Declarative knowledge
expressed through statements that can be shown to be true or false
prototypical example is mathematical logic
Tacit knowledge
Unconscious knowledge that can be difficult to express in words or other representations

24. Other Types of Knowledge
Priori knowledge
independent on experience or empirical evidence
General behavior or trend based
e.g. “All bachelors are unmarried”
Posteriori knowledge
dependent of experience or empirical evidence
e.g. “X was born in 1983”

25. Other Types of Knowledge
Meta knowledge: Knowledge about knowledge, e.g., the knowledge that blood pressure is more important for diagnosing a medical condition than eye color.

26. Knowledge and its types
Factual
Tacit
Procedural
Heuristic
Declarative
Meta-knowledge
Subjective
Priori-Knowledge
Posteriori- Knowledge