Sophia: A Persistent Agent Framework of Artificial Life (arxiv.org)

A new framework called "Sophia" has been introduced to enhance the capabilities of large language models (LLMs) by transforming them into persistent, decision-making agents. Traditional AI architectures have primarily focused on task-specific applications, often lacking a structure to maintain a coherent identity and adapt over time. Sophia proposes a third stratum, termed System 3, which enables agents to maintain a narrative identity and align actions with long-term objectives. This is achieved through four synergistic mechanisms: process-supervised thought search, narrative memory, user and self-modeling, and a hybrid reward system. The significance of this development lies in its potential to bridge the gap between simple and complex task execution, achieving an 80% reduction in reasoning steps for recurring operations and a 40% increase in success rates for high-complexity tasks. By integrating psychological constructs into a computational framework, Sophia provides a novel approach to artificial life that emphasizes identity continuity and transparent behavioral explanations. Although primarily conceptual at this stage, Sophia's engineering prototype signals a meaningful advancement in creating more autonomous and reflective AI systems capable of self-improvement and adaptive learning.