EXPERT SYSTEMS Introduction Characteristics Advantages Limitations MS 204U

EXPERT SYSTEMS • Introduction • Characteristics • Advantages • Limitations MS 204/U 1/L 7/Ashima

Artificial intelligence Vision systems Learning systems Robotics Expert systems Neural networks Natural language processing MS 204/U 1/L 7/Ashima

Artificial Intelligence Duplication of human thought process by machine – Learning from experience – Rapid response to varying situations – Applying reasoning to problem-solving – Manipulating environment by applying knowledge – Thinking and reasoning

Artificial Intelligence Concepts Expert systems – Human knowledge stored on machine for use in problem solving • Natural language processing – Allows user to use native language instead of English • Speech recognition – Computer understanding spoken language • Sensory systems – Vision, tactile, and signal processing systems • Robotics – Sensory systems combine with programmable electromechanical device to perform manual labor

Experts – Have special knowledge, judgment, and experience – Can apply these to solve problems • Higher performance level than average person • Faster solutions • Recognize patterns • Acquired from reading, training, practice

Expert Systems Features Expertise – Capable of making expert level decisions • Symbolic reasoning – Knowledge represented symbolically – Reasoning mechanism symbolic • Self-knowledge – Able to examine own reasoning – Explain why conclusion reached – Knowledge base contains complex knowledge

Example of Expert Systems DENDRAL – Applied knowledge or rule-based reasoning commands – Deduced likely molecular structure of compounds MYCIN – Rule-based system for diagnosing bacterial infections XCON – Rule-based system to determine optimal systems configuration Credit analysis – Ruled-based systems for commercial lenders Pension fund adviser – Knowledge-based system analyzing impact of regulation and conformance requirements on fund status

Applications Finance – Insurance evaluation, credit analysis, tax planning, financial planning and reporting, performance evaluation • Data processing – Systems planning, equipment maintenance, vendor evaluation, network management • Marketing – Customer-relationship management, market analysis, product planning • Human resources – HR planning, performance evaluation, scheduling, pension management, legal advising • Manufacturing – Production planning, quality management, product design, plant site selection, equipment maintenance and repair

EXPERT SYSTEMS Expert systems are designed to solve real problems in a particular domain that normally would require a human expert. It can solve many types of problems Developing an expert system involves extracting relevant knowledge from human experts in the area of problem, called domain experts. MS 204/U 1/L 7/Ashima

Evolution of Expert Systems Software Expert system shell Collection of software packages & tools to design, develop, implement, and maintain expert systems Ease of use high low Traditional programming languages Before 1980 MS 204/U 1/L 7/Ashima Special and 4 th generation languages 1980 s 1990 s Expert system shells

Characteristics of ES Expert system is capable of handling challenging decision problems and delivering solutions. Expert system uses knowledge rather than data for solution. Much of the knowledge is heuristicbased rather than algorithmic. Expert system has the capability to explain how the decision was made. MS 204/U 1/L 7/Ashima

Problem Domain vs. Knowledge Domain An expert’s knowledge is specific to one problem domain – medicine, finance, science, engineering, etc. The expert’s knowledge about solving specific problems is called the knowledge domain. The problem domain is always a superset of the knowledge domain. MS 204/U 1/L 7/Ashima

Problem and Knowledge Domain Relationship MS 204/U 1/L 7/Ashima

Representing the Knowledge The knowledge of an expert system can be represented in a number of ways, including IFTHEN rules: IF you are hungry THEN eat MS 204/U 1/L 7/Ashima

Rules for a Credit Application Mortgage application for a loan for Rs. 100, 000 to Rs. 200, 000 If there are no previous credits problems, and If month net income is greater than 4 x monthly loan payment, and If down payment is 15% of total value of property, and If net income of borrower is > Rs. 25, 000, and If employment is > 3 years at same company Then accept the applications Else check other credit rules MS 204/U 1/L 7/Ashima

Advantages of ES It enhances decision quality. It reduces the cost of consulting experts for problem solving. It provides quick and efficient solutions to problems in narrow area of specialization. It offers high reliability of expert suggestions or decisions. MS 204/U 1/L 7/Ashima

Advantages of ES contd… It can tackle very complex problems that are difficult for human experts to solve. It can work on standard computer hardware. It can not only give solutions, but also the decision logic and how the solution was arrived at. MS 204/U 1/L 7/Ashima

Limitations of ES The knowledge base may not be complete Each problem is different. Hence the solution from a human expert too may be different Expensive to build and maintain Takes long time to develop and fine tune ES Large ES is difficult to build and maintain MS 204/U 1/L 7/Ashima

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