Data-based optimal control of logical networks

Data-driven methods have been recently introduced in the analysis of Boolean control networks (BCNs), with the goal of assessing the solvability of key control problems, even in the absence of a known model, provided that a sufficiently rich data set collected from the network is available. In this paper, we focus on the finite-horizon and infinite-horizon optimal control problems for BCNs and investigate when the collected data allow us to solve the problems and comment on the sub-optimality of the obtained solutions.