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Expert Systems


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Expert Systems

  1. 1. Expert SystemsDirectors : Prof. Zixing Cai &Miss WenShaCentral South UniversityCollege of Information Scienceand Engineering
  2. 2. What is an Expert System?Experts are people who are very familiarwith solving specific types of problems.Expert SystemUntil now, no unified definition has beengiven.Knowledge-based systemThe fundamental function of the expertsystem depends upon its knowledge,therefore, the expert system is sometimes Ccalled knowledge-based system. C IS I Central South University Artificial Intelligence
  3. 3. What is an Expert System(ES)? Definition 1: ES can handle real-world complex problems which need an expert’s interpretation andIn short, an by using a computer model of solve problems ES is an intelligent human expert reasoning to reach the same computer program that can conclusions that the human expert would do if heperform special and difficult task(s) or she faces with a comparable problem. Definition 2: ES is an intelligent computer program in some field(s) at the level of to that uses knowledge and inference procedures human experts. solve problems that are difficult enough to require significant human expertise for their solutions. C IS IC Central South University Artificial Intelligence
  4. 4. Architecture of ideal expert systemUser Communication Knowledge Interface Base Interpreter Plan Planner Agenda Coordinator Solution Adjuster Reasoning Blackboard Machine IS IC Architecture of an ideal expert system C Central South University Artificial Intelligence
  5. 5. ES-Knowledge Base(1)Knowledge Base To store knowledge from the experts ofspecial field(s). It contains facts and feasibleoperators or rules for heuristic planning andproblem solving. The other data is stored in a separatedatabase called global database, ordatabase simply. C IS IC Central South University Artificial Intelligence
  6. 6. ES-Reasoning Machine(2)Reasoning Machine To memorize the reasoning rules and thecontrol strategies applied. According to the information from theknowledge base, the reasoning machine cancoordinate the whole system in a logicalmanner, draw inference and make adecision. C IS IC Central South University Artificial Intelligence
  7. 7. ES- User Interface (3)User Interface To communicate between the user andthe expert system. The user interacts with the expert systemin problem-oriented language such as inrestricted English, graphics or a structureeditor. The interface mediates informationexchanges between the expert system andthe human user. C IS IC Central South University Artificial Intelligence
  8. 8. ES- Interpreter(4)Interpreter Through the user interface, interpreterexplains user questions, commands andother information generated by the expertsystem, including answers to questions,explanations and justifications for itsbehavior, and requests for data. C IS IC Central South University Artificial Intelligence
  9. 9. ES-Blackboard (5)Blackboard To record intermediate hypotheses anddecisions that the expert systemmanipulates. C IS IC Central South University Artificial Intelligence
  10. 10. ES-NoteNote: Almost no exiting expert system containsall the components shown above, but somecomponents, especially the knowledge baseand reasoning machine, occur in almost allexpert systems. Many ESs use global database in place ofthe blackboard. The global databasecontains information related to specific tasksand the current state. C IS IC Central South University Artificial Intelligence
  11. 11. Building Expert SystemThe key for successfully building an expertsystem is to begin it from a smaller one, andextend and test it step by step, make it intoa larger-scale and more perfect system.The general procedure for building ESs :Design of initial Knowledge BaseDevelopment & test for prototype 原型systemImprovement & induction 归纳 for the C IS ICknowledgeUniversity Artificial Intelligence Central South
  12. 12. Design of initial Knowledge BaseProblem identificationKnowledge conceptualizationConcept formulizationRule formulationRule validation C IS IC Central South University Artificial Intelligence
  13. 13. Stages for Designing KB define key concept of the Re-designment knowledge ,for example : identify what the problem use knowledge change the knowledge to check the type of data structure , is , how to define it , can representation programming language of correctness conditions that have known, we divide it into some sub RefinementsQuestions Knowledge Concepts method to represent can be identified by the goal state, assumption that rules or problems the Structure knowledge. the computer. knowledge and control strategy. Rules Indentifi- Conceptu- Formali- Rule Validation cation alization zation Formalization Concepts Conclusion Representation Stages for designing knowledge base C IS IC Central South University Artificial Intelligence
  14. 14. Types of Expert System (ES) Category Problem AddressedInterpretation Inferring situation descriptions from sensor dataPrediction Inferring likely consequences of given situationDiagnosis Inferring system malfunction from observationDesign Configuring objects under constrainsPlanning Designing actionsMonitoring Comparing observation to plan vulnerabilitiesDebugging Prescribing remedies for malfunctionRepair Executing a plan to administer a prescribed remedyInstruction Diagnosing, debugging and repairing student behaviorControl C IS IC Interpreting, predicting, repairing and monitoring system behavior Central South University Artificial Intelligence
  15. 15. Expert Control SystemsImportant differences between expert systems andexpert control systems:Expert systems simply complete consultativefunction for problems of special domains and aidusers to work.Expert control systems need to make decisions tocontrol action independently and automatically.Expert systems usually work in off-line mode.Expert control systems need to acquire dynamicinformation in on-line mode and make real-timeC IS Icontrol for the system. C Central South University Artificial Intelligence
  16. 16. Two main types of expert control Two main types of expert control: Expert control system With a more complex structure, higher cost, better performance, and used to plants or processes where higher technical requirements are needed. Expert controller With a simpler structure, lower cost and has a performance that can meet the general requirements for the industrial process control. C IS IC Central South University Artificial Intelligence
  17. 17. Structures of Expert Control System Operator InterfaceController Reasoning Machine Domain Date Control Knowledge Base DigitalAlgorithms Processing D/A A/DActuators Process Sensors C A typical structure of expert control system IS IC Central South University Artificial Intelligence
  18. 18. Tasks of Expert Control System The expert control system should execute following tasks: Supervise the operation of the plant (process) and controller. Examine possible failure or fault of the system components, replace these faulty components or revise control algorithms to keep the necessary performance of the system. In special cases, select suitable control algorithm to adapt the variation of the system parameters and environment. S IC CI Central South University Artificial Intelligence
  19. 19. Store the domain knowledge of industrial process control,experience Extract and process of experts(expertise) and Expert Controller Use the forward chaining Sum up every control facts information, provide reasoning to judge the Knowledge Base (KB) pattern and control control strategy and learn conditions of every rule in experience of the adaptation with foundation the sequence controlled process K G Feature e Recognition S Inference I Set of U Y Engine (IE) Control Rules PlantR Information - Processing u Sensor(s) Industrial expert controller C IS IC Central South University Artificial Intelligence
  20. 20. Expert system-MYCINAn early expert system developed in early1970s at Stanford UniversityWrote by Lisp LanguageAuthor: Bruce G. Buchanan & Edward H.Shortliffe <<Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project >>This expert system was designed to identifybacteria causing severe infections C IS IC Central South University Artificial Intelligence
  21. 21. C IS ICCentral South University Artificial Intelligence
  22. 22. Reasoning & Problem solving strategyMYCIN could use backward chaining to find outwhether a possible bacteria was to blame.“Certainty factor” is used for an assessment of thelikelihood 可能性评估 of one bacteria.MYCIN’s problem solving strategy was simple: For each possible bacteria: Using backward chaining, try to prove that it is the case, finding the certainty. Find a treatment which ” covers” all the bacteria above some level of certainty. IC CIS Central South University Artificial Intelligence
  23. 23. MYCIN: Problem SolvingWhen trying to prove a goal through backwardchaining, system could ask user certain questions.Certain facts are marked as “askable”, so if theycouldn’t be proved, ask the user.The ask procedure is carried out in following styleof dialogue: MYCIN: Has the patient had neurosurgery? USER: No. MYCIN: IS the patient a burn patient? USER: No. … MYCIN: It could be Diplococcus.. C IS IC Central South University Artificial Intelligence
  24. 24. Modeling Human Diagnostic StrategiesProblem Solving Strategy used in MYCINonly works when small number ofhypotheses (e.g., bacteria).For hundreds of possible diseases, need abetter strategy.Later medical diagnostic systems used anapproach based on human expertreasoning. C IS IC Central South University Artificial Intelligence
  25. 25. Diagnostic Reasoning: InternistInternist is a medical expert system forgeneral disease diagnosis.Knowledge in system consists of diseaseprofiles 概况 , giving symptoms 症状 associatedwith disease and strength of association. C IS IC Central South University Artificial Intelligence
  26. 26. Problem Solving in InternistUse initial data (symptoms) to suggest, or trigger 引发 possible diseases.Determine what other symptoms would beexpected to confirm these diseases.Gather more data to differentiate 区分 betweenthese hypotheses. Either: If one hypothesis most likely, try to confirm it. If many possible hypotheses, try to throw some out. If a few hypotheses, try to discriminate 区别 between IS IC them. C Central South University Artificial Intelligence
  27. 27. Medical Expert Systems TodayMedical expert systems were quite effective inevaluations comparing their performance withhuman experts.Support the physicians 医生 decisions, rather thandoing the whole diagnosis.Include many useful support materials 辅助材料 , suchas report generating tools, reference material etc. C IS IC Central South University Artificial Intelligence
  28. 28. Summary: Expert SystemsEffective systems have been developed thatcapture expert knowledge in areas like medicine.Typically combine rule-based approaches, withadditional certainty/probabalistic reasoning, andsome top level control of the problem solvingprocess.Not a huge take-up of systems, perhaps due tofailure to adequately consider how they would beintegrated into current practice. C IS IC Central South University Artificial Intelligence