IRAM-Omega-Q: A Computational Architecture for Uncertainty Regulation in Artificial Agents

• URL: http://arxiv.org/abs/2603.16020v1
• Date: Mon, 16 Mar 2026 23:58:11 GMT
• Title: IRAM-Omega-Q: A Computational Architecture for Uncertainty Regulation in Artificial Agents
• Abstract summary: We present IRAM-Omega-Q, a computational architecture that models internal regulation as closed-loop control over a quantum-like state representation.<n>Results support uncertainty regulation as a concrete architectural principle for artificial agents.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Artificial agents can achieve strong task performance while remaining opaque with respect to internal regulation, uncertainty management, and stability under stochastic perturbation. We present IRAM-Omega-Q, a computational architecture that models internal regulation as closed-loop control over a quantum-like state representation. The framework uses density matrices instrumentally as abstract state descriptors, enabling direct computation of entropy, purity, and coherence-related metrics without invoking physical quantum processes. A central adaptive gain is updated continuously to maintain a target uncertainty regime under noise. Using systematic parameter sweeps, fixed-seed publication-mode simulations, and susceptibility-based phase-diagram analysis, we identify reproducible critical boundaries in regulation-noise space. We further show that alternative control update orderings, interpreted as perception-first and action-first architectures, induce distinct stability regimes under identical external conditions. These results support uncertainty regulation as a concrete architectural principle for artificial agents and provide a formal setting for studying stability, control, and order effects in cognitively inspired AI systems. The framework is presented as a technical model of adaptive regulation dynamics in artificial agents. It makes no claims regarding phenomenological consciousness, and the quantum-like formalism is used strictly as a mathematical representation for structured uncertainty and state evolution.

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