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dc.contributor.author | Cerone, Antonio![]() |
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dc.contributor.author | Pluck, Graham![]() |
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dc.date.accessioned | 2022-02-07T08:03:18Z | |
dc.date.available | 2022-02-07T08:03:18Z | |
dc.date.issued | 2021-03 | |
dc.identifier.citation | Cerone, A., & Pluck, G. (2021). A Formal Model for Emulating the Generation of Human Knowledge in Semantic Memory. From Data to Models and Back, 104–122. https://doi.org/10.1007/978-3-030-70650-0_7 | en_US |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/6025 | |
dc.description.abstract | The transfer of information processed by human beings from their short-term memory (STM) to their semantic memory creates two kinds of knowledge: a semantic network of associations and a structured set of rules to govern human deliberate behaviour under explicit attention. This paper focuses on the memory processes that create the first of these two kinds of knowledge. Human memory storage and processing are modeled using the Real-time Maude rewrite language. Maude’s capability of specifying complex data structures as many sorted algebras and the time features of Real-Time Maude are exploited for (1) providing a means for formalising alternative memory models, (2) modelling in silico experiments to compare and validate such models. We aim at using our model for the comparison of alternative cognitive hypothesis and theories and the analysis of interactive systems. | en_US |
dc.language.iso | en | en_US |
dc.publisher | From Data to Models and Back | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | Type of access: Open Access | en_US |
dc.subject | Cognitive science | en_US |
dc.subject | Human memory models | en_US |
dc.subject | Formal methods | en_US |
dc.subject | Rewriting logic | en_US |
dc.subject | Real-Time Maude | en_US |
dc.title | A FORMAL MODEL FOR EMULATING THE GENERATION OF HUMAN KNOWLEDGE IN SEMANTIC MEMORY | en_US |
dc.type | Conference Paper | en_US |
workflow.import.source | science |
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