Publications

Paper 1IRAM-Ω-Q: A Computational Architecture for Uncertainty Regulation in Artificial AgentsThis paper introduces the IRAM-Ω-Q framework: a computational model for studying how artificial agents regulate uncertainty, disturbance, and instability over time.Read on arXiv⸻Paper 2Forthcoming / under submissionPaper 2 extends the IRAM-Ω-Q framework by comparing anticipatory and reactive regulation. It studies how the timing of control affects stability, regulatory demand, and the agent’s response to disturbance.Link will be added after submission.⸻Paper 3In preparationPaper 3 studies switching between regulatory modes. It examines whether intermittent anticipatory control can produce carryover effects, reducing the average regulatory effort needed to maintain stability.⸻Paper 4In preparationPaper 4 explores noise in adaptive artificial agents. It examines how different forms of disturbance, including internal and induced noise, affect regulation, stability, and the agent’s ability to recover from perturbation.⸻BookCritical Attention Systems is preparing a research book on attention, regulation, stability, and artificial agents.The book introduces the IRAM-Ω-Q research program in clear, accessible language, connecting simulation-based models of uncertainty regulation with broader questions in AI, adaptive control, and contemplative science.It examines how artificial agents may stabilize attention, recover from disturbance, and regulate internal uncertainty over time.An early-access edition is planned through Critical Attention Systems Publications.← Back to Critical Attention Systems