1. Chapter 4 Knowledge Representation 323-670 Artificial Intelligence ดร. วิภาดา เวทย์ประสิทธิ์ ภาควิชาวิทยาการคอมพิวเตอร์ คณะ วิทยาศาสตร์ มหาวิทยาลัยสงขลานครินทร์

2. 323-670 Artificial Intelligence Lecture 13Page 2 Representations and Mappings  Fact  Representations of facts Spot is a dog. dog(spot)  X: dog(X)  hastail(X) All dogs have tails. Every dog has a tail. hastail(spot) Spot has a tail.

3. 323-670 Artificial Intelligence Lecture 13Page 3 Mapping between Facts and Representations

4. 323-670 Artificial Intelligence Lecture 13Page 4 Representation Of Facts generate appropriate final facts

5. 323-670 Artificial Intelligence Lecture 13Page 5 Approaches to Knowledge Representation  Representational Adequacy : all kinds of knowledge in the domain  Inferential Adequacy : derive new structures corresponding to new knowledge inferred from old  Inferential Efficiency : incorporate into the knowledge structure for the most promising direction  Acquisitional Efficiency : acquire new knowledge easily

6. 323-670 Artificial Intelligence Lecture 13Page 6 Simple Relational Knowledge  Represent set of attribute and associate value  Used in database system  Weak inferential capacity  Use as input for more powerful inference engines

7. 323-670 Artificial Intelligence Lecture 13Page 7 Inheritable Knowledge  Property inheritance : element of specific classes inherit attributes and values from more general classes  Generalization hierarchy  Slot-and-filler structure  Semantic network : chapter 9  Frames : chapter 9

8. 323-670 Artificial Intelligence Lecture 13Page 8 Inheritable Knowledge  Baseball knowledge  isa : show class inclusion  instance : show class membership