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A developer shares Helix-AGI, a continuously-running cognitive agent using a physics-based memory retrieval system that integrates recency, structural importance, and semantic proximity via an entropic gravity equation and Euler-Lagrange dynamics, without tuning separate weights.
The paper introduces Cognitive Agent Compilation (CAC), a framework that uses teacher LLMs to compile problem-solving knowledge into explicit, inspectable agents for educational applications. It aims to address the lack of controllability and explainability in standard LLMs by separating knowledge representation from policy and verification rules.