Understanding human learning using a multi-agent simulation of the Unified Learning Model

Vlad Chiriacescu, Leen Kiat Soh, Duane F. Shell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Within cognitive science. computational modeling based on cognitive architectures has been an important approach to addressing questions of human cognition and learning. This paper reports on a multi-agent computational model based on the principles of the Unified Learning Model (ULM). Derived from a synthesis of neuroscience, cognitive science, psychology, and education, the ULM merges a statistical learning mechanism with a general learning architecture. Description of the single agent model and the multi-agent environment which translate the principles of the ULM into an integrated computational model is provided. Validation results from simulations with respect to human learning are presented. Simulation suitability for cognitive learning investigations is discussed. Multi-agent system performance results are presented. Findings support the ULM theory by documenting a viable computational simulation of the core ULM components of long-term memory, motivation, and working memory and the processes taking place among them. Implications for research into human learning and intelligent agents are presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013
Pages143-152
Number of pages10
DOIs
StatePublished - 2013
Event12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013 - New York, NY, United States
Duration: Jul 16 2013Jul 18 2013

Publication series

NameProceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013

Conference

Conference12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013
CountryUnited States
CityNew York, NY
Period7/16/137/18/13

Keywords

  • Cognitive modeling
  • Computational simulation
  • Human Learning
  • Unified Learning Model

ASJC Scopus subject areas

  • Information Systems
  • Software

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    Chiriacescu, V., Soh, L. K., & Shell, D. F. (2013). Understanding human learning using a multi-agent simulation of the Unified Learning Model. In Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013 (pp. 143-152). [6622237] (Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013). https://doi.org/10.1109/ICCI-CC.2013.6622237