Connectionist expert systems are artificial neural network (ANN) based expert systems where the ANN generates inferencing rules e.g., fuzzy-multi layer perceptron where linguistic and natural form of inputs are used. Apart from that, rough set theory may be used for encoding knowledge in the weights better and also genetic algorithms may be used to optimize the search solutions better. Symbolic reasoning methods may also be incorporated (see hybrid intelligent system). (Also see expert system, neural network, clinical decision support system.)
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References
- Sun, Ron (1994). Integrating rules and connectionism for robust commonsense reasoning. Hoboken, N.J: Wiley & Sons. ISBN 0-471-59324-9.
External links
- Gallant, Stephen I. (February 1988). "Connectionist expert systems". Comm. ACM. 31 (2): 152–69. doi:10.1145/42372.42377. S2CID 12971665.
- resource page: http://www.cogsci.rpi.edu/~rsun/reason.html
- Leão Bde F, Reátegui EB (1993). "HYCONES: a hybrid connectionist expert system". Proc Annu Symp Comput Appl Med Care: 461–5. PMC 2248551. PMID 8130516.
- Barton JG, Lees A (October 1995). "Development of a connectionist expert system to identify foot problems based on under-foot pressure patterns". Clin Biomech (Bristol, Avon). 10 (7): 385–391. doi:10.1016/0268-0033(95)00015-D. PMID 11415584.
- Brasil LM, de Azevedo FM, Barreto JM (September 2001). "Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing". Int J Med Inform. 63 (1–2): 19–30. doi:10.1016/S1386-5056(01)00168-X. PMID 11518662.
- Wei JH (2003). "[Application prospect of human-artificial intelligence system in future manned space flight]". Space Med Med Eng (Beijing) (in Chinese). 16 (Suppl): 482–5. PMID 14989301.
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