  In this note we propose a new approach towards solving numerically optimal
stopping problems via reinforced regression based Monte Carlo algorithms. The
main idea of the method is to reinforce standard linear regression algorithms
in each backward induction step by adding new basis functions based on
previously estimated continuation values. The proposed methodology is
illustrated by a numerical example from mathematical finance.
