A Multi-Timescale Recursive Self-Improvement Engine for Open-Ended Persona Growth
AutoPersonas introduces a multi-timescale engine to prevent long-term persona agents from collapsing into old patterns. It separates controlled divergence from evidence absorption using an OSO loop and five mechanisms. This allows for continuous, open evolution while maintaining a recognizable identity by managing how new information revises the agent's state.