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A FORMAL MODEL FOR EMULATING THE GENERATION OF HUMAN KNOWLEDGE IN SEMANTIC MEMORY

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dc.contributor.author Cerone, Antonio
dc.contributor.author Pluck, Graham
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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Attribution-NonCommercial-ShareAlike 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States