Learning and organization of memory for evolving patterns
O. Schnaack, L. Peliti, A. Nourmohammad
This paper develops a theoretical framework using artificial neural networks to analyze optimal memory strategies for static and evolving patterns, finding that compartmentalized networks are better for dynamic patterns.
bioRxiv · Jun 4, 2021Evolutionary Biology