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dc.contributor.author Chinthanie, W
dc.contributor.author Karunananda, A
dc.contributor.author Dias, N
dc.date.accessioned 2023-03-03T09:08:37Z
dc.date.available 2023-03-03T09:08:37Z
dc.date.issued 2020
dc.identifier.citation Weerakoon, C., Karunananda, A., & Dias, N. (2020). Human-mind-inspired processing model for computing. Mind & Society, 19(2), 237–256. https://doi.org/10.1007/s11299-020-00236-2 en_US
dc.identifier.issn 1860-1839 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/20664
dc.description.abstract Among various computing models, it is difficult to find a model inspired from the human mind to improve the computational efficiency of the computer. In fact, the human mind becomes competent in responding for the inputs, resourcefully and mindfully acquiring knowledge and experience over continuous processing with the time. Further, as it is possible to find deeper explanation for the human mind in the Buddhism, the introduction of a computing model imitating the human mind based on Buddhist Theory of Mind (BTM) to enhance the computational efficiency, would be a great research challenge. According to the BTM, human mind is a continuous thought process which arise as per the conditions. Imitating this processing model in the human mind, a computing model called Six-state Continuous Processing model was introduced exploiting 24-causal relations in BTM. This paper discusses this profound Buddhist theoretical approach that was used in order to derive the Six-state continuous processing model. en_US
dc.language.iso en_US en_US
dc.publisher Springer en_US
dc.subject Nature inspired computing en_US
dc.subject Six-state continuous processing model en_US
dc.subject Memory en_US
dc.subject NP-completeness en_US
dc.subject Buddhist Theory of Mind en_US
dc.subject Thought process en_US
dc.subject 24 causal relations en_US
dc.title Human-mind-inspired processing model for computing en_US
dc.type Article-Full-text en_US
dc.identifier.year 2020 en_US
dc.identifier.journal Mind & Society en_US
dc.identifier.issue 2 en_US
dc.identifier.volume 19 en_US
dc.identifier.database Springer Link en_US
dc.identifier.pgnos 237-256 en_US
dc.identifier.doi 10.1007/s11299-020-00236-2 en_US


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