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Expert System Implemented for Problem Solving in Commerce/business Domain
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The application of Expert Systems in commerce/business domain is relatively new research area. The rapid growth of artificial intelligence has lead to the development and implementation of expert systems for the purpose of commerce/business problem solving. This generated a need for analysis and review of Expert Systems in commerce/business domain. Here a few expert systems already implemented in the area of resource allocation/ space utilization are reviewed. In addition, analysis is provided based on the following factors: Objective of system, need for the system, development environment, heuristics used, user interaction, knowledge base, explanation facility, inference engine, knowledge update facility, performance evaluation, and category of expert system. At the end, comparisons between expert systems based on the above factors are provided. Though complete comparison is not possible, because each expert system is supposed to be expert in its own domain and work in the specified domain with given constraints. Still comparison enabled me to identify the factors which should be considered for the development of expert system in human resource area. The main objective of the analysis and review is to be acquainted with knowledge to develop Expert System in other domains. At the end of the paper, guidelines for developing Expert Systems are presented.
Keywords
Expert Systems, Explanation Facility, Inference Engine, Knowledge Update Facility, Resources Allocation
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- David Rolston, (1988), “principles of artificial intelligence and expert systems development”, Tata McGraw Hill, Chap-1, page 1.
- Davis, (1985), “problem solution with expert system”, Texas instruments, Dallas.
- Ehud Gudes, Tsvi Kuflik and Amnon Meisels, (1990), “An Expert System Based Methodology for Solving Resource Allocation Problems”, ACM 089791-372- 8/90/007/0309.
- Ron Lemaster, (1990), “ALEX- An Expert System for Truck Loading”, IBM Commercial Systems Integration Boulder, ACM 089791-372-8/90/0007/0638.
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