Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments

This research introduces Adaptive Memory Crystallization (AMC), a novel memory architecture designed for autonomous AI agents to progressively consolidate experiences in dynamic environments without forgetting prior knowledge. AMC models memory as a continuous crystallization process across a three-phase hierarchy, inspired by synaptic tagging and capture theory and governed by stochastic differential equations.