artificial intelligence knowledge representation

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Artificial Intelligence Knowledge Representation

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Page 1: Artificial Intelligence Knowledge Representation

Artificial Intelligence

Knowledge Representation

Page 2: Artificial Intelligence Knowledge Representation

Introduction

Page 3: Artificial Intelligence Knowledge Representation

Introduction Cont.

Page 4: Artificial Intelligence Knowledge Representation

Data-Information-Knowledge-Wisdom

Page 5: Artificial Intelligence Knowledge Representation

Data-Information-Knowledge-Wisdom

Page 6: Artificial Intelligence Knowledge Representation

The AI Cycle

Page 7: Artificial Intelligence Knowledge Representation

Knowledge and its types

• Durkin refers to it as the “Understanding of a subject area”.

There are different types of knowledge• Procedural knowledge• Declarative • Meta knowledge• Heuristic knowledge• Structural knowledge

Page 8: Artificial Intelligence Knowledge Representation

Types of knowledge (Cont.)

Page 9: Artificial Intelligence Knowledge Representation

Procedural VS Declarative Knowledge

Page 10: Artificial Intelligence Knowledge Representation

Types of Knowledge Cont.• 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: It describes objects, rather than processes. What

is known about a situation, e.g. it is sunny today, and cherries are red.• Meta knowledge: Knowledge about knowledge, e.g., the knowledge that

blood pressure is more important for diagnosing a medical condition than eye color.

• Heuristic knowledge: Rule-of-thumb, e.g. if I start seeing shops, I am closeto the market.o Heuristic knowledge is sometimes called shallow knowledge.o Heuristic knowledge is empirical as opposed to deterministic

• Structural knowledge: Describes structures and their relationships. e.g.how the various parts of the car fit together to make a car, or knowledge structures in terms of concepts, sub concepts, and objects.

Page 11: Artificial Intelligence Knowledge Representation

Knowledge Representation

Page 12: Artificial Intelligence Knowledge Representation

Knowledge Representation

• Pictures and symbols. This is how the earliest humans represented knowledge when sophisticated linguistic systems had not yet evolved

• Graphs and Networks• Numbers• Descriptive

Page 13: Artificial Intelligence Knowledge Representation

Using Picture

• As you can see, this kind of representation makes sense readily to humans, but if we give this picture to a computer, it would not have an easy time figuring out the relationships between the individuals, or even figuring out how many individuals are there in the picture. Computers need complex computer vision algorithms to understand pictures.

Page 14: Artificial Intelligence Knowledge Representation

Using a graph and description

Using a description in wordsFor the family above, we could say in words– Tariq is Mona’s Father– Ayesha is Mona’s Mother– Mona is Tariq and Ayesha’s Daughter

Page 15: Artificial Intelligence Knowledge Representation

Formal KR techniques

• Facts• Rules• Semantic Nets• Frames• Logic

Page 16: Artificial Intelligence Knowledge Representation

Facts

• Single-valued• multiple –valued• Uncertain facts• Fuzzy facts• Object-Attribute-Value triplets

Page 17: Artificial Intelligence Knowledge Representation

Rules

• Relationship• Recommendation• Directive• Uncertain Rules• Meta Rules• Rule Sets

Page 18: Artificial Intelligence Knowledge Representation

Semantic networksSemantic networks are graphs, with nodes representing objects and arcs representing relationships between objects. Various types of relationships may be defined using semantic networks. The two most common types of relationships are–IS-A (Inheritance relation)–HAS (Ownership relation)