Point-based value iteration for partially-observed Boolean dynamical systems with finite observation space

This paper is concerned with obtaining the infinite-horizon control policy for partially-observed Boolean dynamical systems (POBDS) when measurements take place in a finite observation space, with application to Boolean gene regulatory networks. The goal of control is to reduce the steady-state mass of undesirable states, which might be associated with disease. The idea behind the proposed method is to transfer the partially-observed Boolean states into a continuous observed state space known as belief space, and then employ the well-known value iteration method based on Point-Based Value Iteration (PBVI). The performance of the method is investigated using a Boolean network model constructed from melanoma gene-expression data observed through Bernoulli noise.