Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawar...
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...