Understanding human learning using a multi-agent simulation of the unified learning model

Vlad Chiriacescu, Leen-Kiat Soh, Duane F. Shell
2013 2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing  
Within cognitive science. computational modeling based on cognitive architectures has been an important ap proach to addressing questions of human cognition and learning. This paper reports on a multi-agent computa tional model based on the principles of the Unified Learn ing Model (ULM). Derived from a synthesis of neurosci ence, cognitive science, psychology, and education, the ULM merges a statistical learning mechanism with a gen eral learning architecture. Description of the single agent
more » ... del and the multi-agent environment which translate the principles of the ULM into an integrated computation al model is provided. Validation results from simulations with respect to human learning are presented. Simulation suitability for cognitive learning investigations is dis cussed. Multi-agent system performance results are pre sented. Findings support the ULM theory by documenting a viable computational simulation of the core ULM com ponents of long-term memory, motivation, and working memory and the processes taking place among them. Im plications for research into human learning and intelli gent agents are presented.
doi:10.1109/icci-cc.2013.6622237 dblp:conf/IEEEicci/ChiriacescuSS13 fatcat:aar6rx32gzfqnjws7dungrmbge