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Knowledge Representation. A knowledge base can be organised in several different configurations to facilitate fast inferencing Knowledge Representation.

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Presentation on theme: "Knowledge Representation. A knowledge base can be organised in several different configurations to facilitate fast inferencing Knowledge Representation."— Presentation transcript:

1 Knowledge Representation

2 A knowledge base can be organised in several different configurations to facilitate fast inferencing Knowledge Representation Schemes designed so that facts and other knowledge contained within then can be used in reasoning Majority are based on models, rules and frames

3 Knowledge Representation Schemes Scripts Decision Tables Lists Models Semantic Networks Production Rules Frames

4 Scripts Describes a sequence of events Elements of a typical script: Props –objects that are used in the sequence of events that occur Roles –the people involved in the script Scenes –describe the actual sequence of events that occur

5 Scripts Useful form of Knowledge representation –so many stereotypical situations Used in case-based reasoning Decision Tables Also called induction tables or knowledge maps Knowledge is collected in knowledge acquisition sessions

6 Lists A written series of related items –names of peoples –shopping list –things to do that week Can be used to represent hierarchical knowledge –objects are grouped, or graded according to rank

7 Modelling Decision trees –Composed of nodes representing goals and links representing decisions All human decision making are based on models of aspects of the world complex, incomplete, difficult to ascertain Computer models are more precise and consistent

8 Models They are written clearly so that they can be understood and criticised They always draw error free logical conclusions from their assumptions They can be changed and tested very quickly

9 When to use Models To organise thoughts and ideas to gain understanding to suggest new ideas and perceptions to aid in the development of theories to predict the consequence of actions to aid in the communication of mental methods

10 Expert Builder Enables the construction of models based on rules The rules are represented in the diagram Diagram can be saved as rules and viewed

11 Semantic Networks Semantic networks are graphic depictions of knowledge composed of nodes and links They show hierarchical relationships between objects Objects can be any physical item –book, car, desk or even a person Objects can also be –concepts, events, actions FIGURE 14.2

12 Production Rules Knowledge is presented as production rules These take the form of condition-action pairs IF condition occurs THEN action Each rule implements a chunk of expertise The quickly become interdependent

13 Rules - Advantages Easy to understand Inferences are easily derived Modifications are relatively easy Rules - Limitations Usually a great number of rules are required Difficult to maintain Difficult to represent all knowledge in terms of rules

14 Frames Structure that includes all the knowledge about a particular object Each Frame describes one object –what it is –How it behaves An application of object-oriented programming for AI and ES Widely used

15 Uncertainty Refers to a wide range of situations where the relevant information is deficient: –information is partial –information is not fully reliable –conflicting information –approximate information Probability may be included in the rules –IF the interest rate is increasing, THEN the price of stocks will decline (80 percent probability)


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