AKMA: Autonomous Knowledge Mutation for Persistent RAG Systems

AKMA (Autonomous Knowledge Mutation Architecture) is a consensus-gated framework for enabling persistent retrieval-augmented generation (RAG) systems to evolve knowledge bases autonomously through user interactions. Unlike conventional RAG architectures that rely on static corpora, AKMA introduces candidate staging, adversarial validation, multi-session consensus verification, and atomic promotion mechanisms to support controlled knowledge evolution while mitigating semantic drift and knowledge poisoning attacks. Experimental evaluation demonstrates autonomous knowledge expansion, mutation validation effectiveness, poisoning resistance, and operational latency characteristics across multiple validation pathways. The framework provides a proof-of-concept foundation for self-evolving knowledge systems operating in dynamic and adversarial environments.