1. Expert System / Knowledge-based System Dr. Ahmed Elfaig 1.ES can be defined as computer application program that makes decision or solves problem in a particular field, by using knowledge and analytical rules defined by experts in the field ( Zohadie 2001) 2.ES can be considered as a knowledge work since it involves manipulation of knowledge. 3.ES involves integrating knowledge into computer program in order to solve complex problem normally requiring a high level of human expertise. 1.ES can be defined as computer application program that makes decision or solves problem in a particular field, by using knowledge and analytical rules defined by experts in the field ( Zohadie 2001) 2.ES can be considered as a knowledge work since it involves manipulation of knowledge. 3.ES involves integrating knowledge into computer program in order to solve complex problem normally requiring a high level of human expertise.

2. Expert System/ Knowledge-based System 1. The basic idea of expert system is to incorporate expertise i.e. information and knowledge and heuristic relevant to a given problem area into software system ( Beck, 1994). 2. ES is computer system that encapsulates specialists’ knowledge a bout a particular domain of expertise and is capable of making decision within that domain ( Durkin, 1994). 3. This process consists of defining the problem, analyzing it and taking a series of sequential and conditional steps to reach some sets of conclusions.

3. Expert System/ Knowledge-based System Knowledge-based systems are software system capable of supporting the explicit representation of knowledge in some specific competence domain and explaining it through appropriate reasoning mechanisms in order to provide high level problem solving performance. ES interprets information and reasons towards a conclusion obtaining the same results that a human expert would arrive at, if presented with a comparable task

4. Expert System/ Knowledge-based System The knowledge-based systems contain expert knowledge about specific domain and are able to apply this knowledge to make a useful inference and provide expert-level advice to user of the system ES contains knowledge-base or database that incorporate specific knowledge for reaching conclusions that a human expert would reach if faced with a comparable problem.

5. Expert System/ Knowledge-based System ES approach aims at analyzing and providing solutions to the problem domain similar to the human experts or better than them

6. ES Performance ES performs many functions just like human does 1. Asking relevant questions 2. Explaining its reasoning 3. ES reason heuristically ( rule of thumb) 4. ES interact with humans in appropriate way 5. ES helps to solve those problems that are traditionally solved using human expert judgment and experiences 6. ES uses to interpret statistics 7. ES capable of explaining and justifying solutions and recommendations to convince the user that its reasoning is correct.

7. ES’s end user End user as question what the expert system does? End user may focus on ES does rather than How? ES emulates Human behavior

8. Expert System Application ( Area) Area of application almost endless Wherever, human expertise is needed to solve problem, ES is likely candidate for application Geology: The famous ES called PROSPECOR used to assist geologist in mineral exploration Medicine: MYCIN was used to assist physician to diagnose infectious blood disease DENDRAL: was designed to perform chemical analysis of soil

9. Expert System Application ( Area) Agriculture: PADI_ES for irrigation project uses TURBO PROLOG 2 This system assists in better water management in paddy irrigation scheme Environment: NOISE expert aims at helping to control the impact of noise emitted from high speed trains. The system uses declarative and heuristic knowledge The rule of the system was built in the forms of if….then syntax

10. Shortcomings in the developed ES Lack of planning ability minimize their utility to characterize and deal with noise ability Lack of prediction ability Such programs have a very specific narrow domain These programs could not use measures of uncertainty for its results The developed Ess are difficult to extend beyond the scope originally determined by their designers.

11. ES domain Problem domain ( identification) 1. Appropriate problem domain is a crucial and critical part of ES development 2. The domain contains the information and knowledge that define the parameters of the problem. Example problem domain: Community Noise Pollution This includes problem identification, analyzing, solution and recommendations.

12. ES Problem Domain Includes: Temporal and spatial dimension of CNP How the community people perceives the problem The sensitive areas that affected by the problem CNP levels CNP effects Factors that contribute to existing noise level Suggest the possible mitigation measures

13. ES Problem Domain Problem domain ( Analysis) Problem domain analysis means division of problem into sub- modules It should reflects that the problem is reasonably complex. The problem should be divided into several sub-modules e.g. 1.Noise level modules 2. noise causes modules 3. noise effects modules 4. Mitigation measures modules This would lead to further sub-modules This lead to predictive models and design of a program that has a planning ability

14. Sources of information and knowledge for ES problem domain The information and knowledge related to these modules would be elicited from: 1.Field work 2.Textual data 3.Knowledge elicited and grabbed from the experts on problem subject area

15. Characteristics of the problem domain suitable for ES Should be solvable problem It does not change quickly Well bounded The qualitative knowledge required by the problem is heuristic and uncertain

16. ES domain Expert For the problem domain 1.The domain contains special knowledge, experiences, methods and judgment 2.The expertise reflects in recognizing and formulating the problem solving 3.The knowledge elicitation from an experts is performed through knowledge engineer ( researcher) as he: a.Serves as intermediary between the domain experts and the system b.Encode the knowledge to be used by the ES c.Transform the knowledge into a form suitable to be used in the expert system

17. Knowledge Domain Emphasizes on the knowledge pertaining to a problem of the research All the knowledge e.g. on noise causes, noise levels, noise effect and life quality modules which are based on noise quality environment. Knowledge domain also contain knowledge on noise mitigation and predictive models Contain facts about the problem area, theories, rules and procedures The facts take the form of declarative knowledge ( true/ false) The heuristics take the form of rules if…then Modification to this domain is important since knowledge is continuously changing and expanding overtime

18. End-user-Domain This domain contains the needs and requirements of the end-users I.e. The user attitudes, expectation and satisfaction of the system User accessibility of the system User interfaces and inserts the facts during a particular session Flexible user interfacing mechanism such: A.Dialogue box B.Slide show C.Select from a list D.Text oriented display E.Explanation facilities ( Why certain information is needed) and how certain conclusion is reached. End user in this system can be class demonstration, town planning unit, highway engineers, Department of environment