1. Second Generation ES1 Second Generation Expert Systems Ahme Rafea CS Dept., AUC

2. Second Generation ES2 First Generation ES Problems Knowledge Acquisition Explanation Brittleness KB Maintenance

3. Second Generation ES3 Multiple Domain Knowledge Models Multiple Domain Models –Different Representation –Deep Knowledge –Qualitative Reasoning –Different Level (e.g. diseases, anatomy,…) –Different Points of View(e.g. Structural and Functional)

4. Second Generation ES4 Multiple Methods Specialized to a particular Representation Specialized for a particular subtask Combine multiple models and methods There are many criteria for choosing a problem-solving architecture Domain Analysis is needed to choose the problem-solving architecture

5. Second Generation ES5 Knowledge Level Distinction between Knowledge Level and Implementation Level Describing the problem-solving process in more abstract terms such as classification, data abstraction, abduction, etc. Emphasizing how the problem will be solved rather that how the system will be implemented Provides guidance in Knowledge Acquisition Reuse of Generic Constructs More abstract Explanation

6. Second Generation ES6 KL Different Approaches Role Limiting Method, putting emphasis on methods Generic Task is a method oriented approach(Limited set of Primitive Constructs) KADS places emphasis on Task (general modeling Language) Model Based Reasoning puts emphasis on Domain Model

7. Second Generation ES7 Second Generation Expert Systems Knowledge Acquisition Explanation Robustness and Efficiency Reusability

8. Second Generation ES8 Knowledge Acquisition Modeling Instantiating the Model Validation Open Issues and On-going Work –Development of the model and acquisition of domain knowledge may be interleaved –Selecting the appropriate model may not be easy

9. Second Generation ES9 Explanation Explaining at the right level of abstraction –The Task structure and the domain model provide the basis for more abstract explanation Re-constructive Explanation –One KBS (performance system) is used to solve the problem, then conclusion of this system is passed to a second system (the explanation system) that justifies(and thus explains ) the conclusion Open Issues –Producing explanation in natural language –Adapting the explanation to user needs –Managing the dialogue

10. Second Generation ES10 Robustness and Efficiency Multiple Knowledge Sources –Representing sufficient knowledge, improve the robustness of the system –Efficiency increases because only necessary knowledge is processed Multiple Representation –Specialized representation, tuned to particular types of knowledge can make certain inferences very tractable Open Issues –Difficulties in integrating diverse knowledge sources and representations

11. Second Generation ES11 Reusability Reusing Knowledge-Level models Reusing Knowledge bases Reusing Symbol-level Components