Universal Meta-Agent Control Systems

<p dir="ltr">This paper presents a novel mathematical theory of intelligent control systems based on a recursive meta-agent architecture. The proposed framework, referred to as the Universal Meta-Agent Control System, formalizes an intelligent structure in which a meta-agent generates chains of parameterized agents that, in turn, control arbitrary objects within a probabilistic and mathematically guaranteed framework. The theory integrates concepts from probability theory, functional analysis, stochastic optimization, and optimal transport geometry (Wasserstein metric). A new universal control theorem is introduced and rigorously proven. It establishes the existence and uniqueness of an invariant measure for the stochastic generator of agents, the almost-sure convergence of locally adaptive learning rules satisfying Robbins–Monro conditions, and the recursive stability of the meta-agent’s generative process. The system ensures that with positive probability, “thinking” agents capable of approximating any admissible control law emerge infinitely often. The proposed meta-intelligent architecture provides a unified mathematical foundation for constructing adaptive, self-generating, and universally convergent control systems applicable to robotics, cyber-physical environments, and complex technical domains.</p><p dir="ltr"><br></p>