recursive, stochastic algorithms which can be applied to economic models with learning. The formal result provides probability … bounds for convergence which can be used to describe the local stability under learning of rational expectations equilibria …

trade the stocks. In this paper, we introduce a Reinforcement Learning based approach to develop a trading agent which … applied different On-policy Reinforcement Learning Algorithms such as Vanilla Policy Gradient (VPG), Trust Region Policy …

barycentric model in the space of probability measures. Moreover, a machine learning type procedure for model selection, based in …

general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the … routines then build solutions to the original problem.In our previous indirect GAs, learning is implicit and is restricted to … needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning …