N. R. Barraza

On the Structural Limits of Machine Learning Decision Systems: An Information-Theoretic, Interaction-Based, and Stochastic-Dynamical Perspective

This work examines intrinsic limits of data-driven decision systems from an information-theoretic and interaction-based perspective and describes decision systems, including LLM-integrated agent architectures, as feedback-driven stochastic processes where state-dependent dynamics may induce emergent macroscopic behavior.