Circular Associative Memory Architecture: A Framework for Emotionally-Keyed AI Memory systems

This paper proposes the Circular Associative Memory Architecture (CAMA), a three-layer framework for organizing AI memory by emotional signature rather than keyword indexing. The architecture consists of a conversation archive, a relational index encoding emotional signatures and relational weight, and a circular active ring enabling emotionally-keyed retrieval. Implementation strategies within existing LLM memory constraints are presented, along with applications to therapeutic AI companionship and a proposed evaluation framework.