Compositional Construction of Safety Controllers for Networks of Continuous-Space POMDPs

In this article, we propose a compositional framework for the synthesis of safety controllers networks partially observable discrete-time stochastic control systems (also known as continuous-space Markov decision processes (POMDPs)). Given an estimator, utilize discretization-free approach to synthesize ensuring specifications over finite-time horizons. The proposed is based on notion so-called local barrier functions computed subsystems in two different ways. first scheme, no prior knowledge estimation accuracy needed. second utilizes probability bound using xmlns:xlink="http://www.w3.org/1999/xlink">stochastic simulation . both schemes, derive sufficient small-gain-type conditions order compositionally construct functions interconnected POMDPs local subsystems. constructed overall enable us compute lower bounds probabilities that avoid certain unsafe regions We demonstrate effectiveness our approaches by applying them adaptive cruise problem.