A Survey of Memory Models for Virtual Humans: From Psychological Foundations to Computational Architectures

Virtual Humans are an advanced class of Virtual Agents characterized by human like embodiment and cognitive capabilities Central to their adaptivity is the integration of computational cognitive architectures in which memory models play a key role in learning continuity and contextual reasoning This review bridges psychological theories of memory and their computational implementations by comparing symbolic and connectionist approaches and exploring new paradigms such as Memory Augmented Neural Networks and Large Language Models We propose a unified framework for analyzing the components of artificial memory Working Semantic Episodic Procedural Spatial and Autobiographical Memory and review their applications in domains such as education games and social simulation Finally we discuss open challenges and future works