IRAM-Omega-Q: A Computational Framework for Uncertainty Regulation in Adaptive Agents 事件

IRAM-Omega-Q: A Computational Framework for Uncertainty Regulation in Adaptive Agents arXiv:2603.16020v2 Announce Type: replace Abstract: Adaptive agents operating under uncertainty must do more than optimize task outputs: they must maintain a workable internal state under noise, perturbation, and changing conditions. This paper introduces IRAM-Omega-Q, a computational framework for modeling uncertainty regulation in adaptive agents under stochastic disturbance. The framework combines a quantum