Maximizing the probability of attaining a target prior to extinction

Debashis Chatterjee (1) , Eugenio Cinquemani (2) , John Lygeros (1)

1 Automatic Control Laboratory [Zurich]
2 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks

We present a dynamic programming-based solution to the problem of maximizing the probability of attaining a target set before hitting a cemetery set for a discrete-time Markov control process. Under mild hypotheses we establish that there exists a deterministic stationary policy that achieves the maximum value of this probability. We demonstrate how the maximization of this probability can be computed through the maximization of an expected total reward until the first hitting time to either the target or the cemetery set. Martingale characterizations of thrifty, equalizing, and optimal policies in the context of our problem are also established.

Domaines: Bio-informatique [q-bio.QM]; Bio-Informatique, Biologie Systémique [q-bio.QM]; Optimisation et contrôle [math.OC]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]; Automatique / Robotique; Systèmes dynamiques [math.DS]

Debashis Chatterjee, Eugenio Cinquemani, John Lygeros. Maximizing the probability of attaining a target prior to extinction. Nonlinear Analysis: Hybrid Systems, 2011, 5, pp.367-381. ⟨10.1016/j.nahs.2010.12.003⟩. ⟨hal-00793042⟩