Expert system, Architecture of Expert systems, Roles of Expert systems

Expert systems
a) Architecture of Expert systems
b) Roles of Expert systems

1. 22MCA262 Artificial Intelligence

2. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

3. What are expert systems? Expert Systems  are computer programs that use knowledge and inference procedures to  solve complex problems  that  normally  require  human expertise . It emulate the decision-making ability of a human  expert. An expert system is divided into two subsystems: Knowledge base , which represents facts and rules; and Inference engine , which applies the rules to the known facts to deduce new facts 5.1) Expert system

4. 5.1) Typical expert system Working of Expert system for Car engine diagnosis : IF engine_getting_petrol AND engine_turns_over THEN problem_with_spark_plugs IF NOT engine_turns_over AND NOT lights_come_on THEN problem_with_battery

5. Typical Tasks for Expert Systems The interpretation of data , Such as sonar data or geophysical measurements Diagnosis of malfunctions , Such as equipment faults or human diseases Structural analysis or configuration of complex objects , Such as chemical compounds or computer systems Planning sequences of actions , Such as might be performed by robots Predicting the future , Such as weather, share prices, exchange rates 5.1) Expert system

6. Characteristics of Expert Systems They simulate human reasoning about the problem domain , rather than simulating the domain itself. They perform reasoning over representations of human knowledge , in addition to doing numerical calculations or data retrieval. They have corresponding distinct modules referred to as the inference engine and the knowledge base. Problems tend to be solved using heuristics (rules of thumb) or approximate methods or probabilistic methods which, unlike algorithmic solutions, are not guaranteed to result in a correct or optimal solution. They provide explanations and justifications of their solutions or recommendations in order to convince the user that their reasoning is correct. 5.1) Expert system

7. Architecture of Expert Systems The process of building expert systems is often called knowledge engineering. The knowledge engineer is involved with all components of an expert system 5.1) Expert system

8. Architecture of Expert Systems 5.1) Expert system

9. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

10. 5.1-b) Roles of Expert system

11. 5.1-b) Roles of Expert system

12. Roles in Expert System Development Three fundamental roles in building expert systems are Expert : Successful ES systems depend on the experience and application of knowledge that the people can bring to it during its development. Large systems generally require multiple experts. Knowledge engineer: The knowledge engineer has a dual task. ( i ) He should be able to elicit knowledge from the expert, gradually gaining an understanding of an area of expertise. (ii) the knowledge engineer must also select a tool appropriate for the project and use it to represent the knowledge. User: A system developed by an end user with a simple shell, is built rather quickly. Larger systems are built in an organized development effort. A prototype-oriented iterative development strategy is commonly used. 5.1-b) Roles of Expert system

13. Architecture of Expert Systems The process of building expert systems is often called knowledge engineering. The knowledge engineer is involved with all components of an expert system 5.1) Expert system

14. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

15. Knowledge Acquisition : The knowledge acquisition component allows the expert to enter their knowledge or expertise into the expert system, and to refine it later as and when required. Stages of knowledge acquisition 5.2) Knowledge acquisition

16. Stages of knowledge acquisition Knowledge identification: Use in depth interviews in which the knowledge engineer encourages the expert to talk about how they do what they do. The knowledge engineer understand the domain to know about objects and facts. Knowledge conceptualization: Find the primitive concepts and conceptual relations of the problem domain. Formalization: Performs Epistemological analysis: Uncover the structural properties of the conceptual knowledge, such as taxonomic relations (classifications). Logical analysis: Decide how to perform reasoning in the problem domain. This kind of knowledge can be particularly hard to acquire. Implementation analysis: Work out systematic procedures for implementing and testing the system. 5.2) Knowledge acquisition

17. 5.2) Roles of Expert system

18. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

19. 5.2. a) Meta knowledge

20. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

21. 5.2-b) Heuristics Heuristics are rule-of-thumb strategies used to simplify decision-making and problem-solving processes. They are not guaranteed to be optimal or perfect but are sufficient for reaching immediate, practical solutions. They help the system to draw inferences, make judgments, and solve problems without having to rely on extensive computational models or exhaustive search.

22. 5.2-b) Heuristics Types of Heuristics: Rule-based heuristics : These are specific if-then rules derived from the knowledge and experience of human experts. Example: In medical diagnosis systems, rules like "If patient has fever and cough, then suspect flu" can be used. Search heuristics : These guide the search through problem spaces to quickly find solutions. Example: In game-playing systems like chess engines, heuristic search algorithms reduce the number of potential moves to evaluate. Evaluation heuristics : These are used to assess or rank possible solutions. Example: In financial advisory systems, heuristic functions might be used to evaluate the risk of different investment strategies.

23. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

24. 5.3-a) MYCIN

25. 5.3-a) MYCIN

26. 5.3-a) MYCIN

27. 5.3-a) MYCINArchitecture

28. 5.3-a) MYCINArchitecture

29. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

30. 5.3-b) DART

31. 5.3-b) DART

32. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

33. 5.3-c) XOON

34. 5.1) Expert systems a) Architecture of Expert systems b) Roles of Expert systems 5.2) Knowledge acquisition a) Meta knowledge b) Heuristics 5.3) Typical expert systems a) MYCIN b) DART c) XOON d) expert system shells Module-5: Expert system

35. 5.3-d) Expert system Shell

36. 5.3-d) Expert system Shell

37. 5.3-d) Expert system Shell Shell components

38. 5.3-d) Expert system Shell

39. 5.3-d) Expert system Shell

40. 5.3-d) Expert system Shell

41. 5.3-d) Expert system Shell

42. 5.3-d) Expert system Shell

43. 5.3-d) Expert system Shell

44. Rule based expert system

45. Rule based expert system