Creating a plausible Unified Theory of Cognition (UTC) requires considerable effort from large, potentially distributed, teams. Computational Cognitive Architectures (CCAs) provide researchers with a concrete medium for connecting different cognitive theories to facilitate development of a robust, unambiguous UTC. However, due to wide dissemination of research effort, and broad scope of cognition as a psychological science, keeping track of CCA contributions is difficult. We compare the structuring of long-term memory (LTM) in two CCAs: ACT-R and CHREST. LTM structuring is considered in particular since it is an essential component of CCAs and underpins most of their operations. We aim to consolidate knowledge regarding LTM structuring for these CCA's and identify similarities and differences between their approaches. We find that, whilst the architectures are similar in a number of ways, providing consensus for some concepts to be included in a UTC, their differences highlight important questions and development opportunities.
|Title of host publication||Proceedings of the 37th Annual Meeting of the Cognitive Science Society|
|Editors||D.C. Noelle, Rick Dale, Anne Warlaumont, Jeff Yoshimi, Teenie Matlock, Carolyn Jennings, Paul P. Maglio|
|Place of Publication||CA, USA|
|Publisher||Cognitive Science Society|
|Number of pages||6|
|Publication status||Published - 2015|