Robust Controllability of Boolean Control Networks via Dynamic Programming

• Published in: IEEE transaction on neural networks and learning systems Vol. PP; pp. 1 - 14
• Main Authors: Li, Yakun, Gao, Shuhua, Gao, Yiming, Wu, Jianliang, Feng, Jun-e, Xiang, Cheng
• Format: Journal Article
• Language: English
• Published: United States IEEE 19.05.2025
• Subjects: Boolean control networks (BCNs); Computational efficiency; Computational modeling; Controllability; Dynamic programming; Heuristic algorithms; Perturbation methods; robust controllability; State feedback; Sufficient conditions; Time complexity; Vectors

This article presents a novel dynamic programming approach to determine the robust controllability of Boolean control networks (BCNs) subject to stochastic disturbances. By applying Bellman's optimality principle, we derive the recurrence relation for computing the optimal time matrix, a crucia...