Predictive Control of Complex Stochastic Systems using Markov Chain Monte Carlo with Application to Air Traffic Control

Markov chain Monte Carlo (MCMC) methods can be used to make optimal decisions in very complex situations in which stochastic effects are prominent. In this paper we briefly introduce our current research on the application of MCMC to the predictive control of complex stochastic systems and the application to air traffic control.