Distributed computation for neural-based abductive reasoning

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dc.contributor.authorRomdhane, LB
dc.contributor.authorElhadef, Mourad
dc.date.accessioned2022-04-08T10:54:24Z
dc.date.accessioned2023-08-19T08:18:08Z
dc.date.available2022-04-08T10:54:24Z
dc.date.available2023-08-19T08:18:08Z
dc.date.issued2005-07
dc.description.abstractThis work extends a recent model for neural-based abductive reasoning to account for the monotonic class. A problem is said to be monotonic some causes, together, explain the same effect. For this, we developed a new computational principle, called the softmin, and implemented it within a neural architecture. Simulation results are very satisfactory and should stimulate future research.en_US
dc.identifier.citationRomdhane, L. B., & Elhadef, M. (2005, July). Distributed computation for neural-based abductive reasoning. In Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. (Vol. 2, pp. 833-838). IEEE.en_US
dc.identifier.doihttps://doi.org/10.1109/IJCNN.2005.1555960
dc.identifier.urihttps://edms.wexl.in/handle/1/3163
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDistributed computationen_US
dc.subjectNeural-based abductive reasoningen_US
dc.subjectMonotonic classen_US
dc.subjectNeural architectureen_US
dc.titleDistributed computation for neural-based abductive reasoningen_US
dc.title.alternativejournal Articalen_US
dc.typeArticleen_US

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