Abstract. We introduce and study the following model for routing uncertain demands through a network. We are given a capacitated multicommodity flow network with a single source an...
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. Optimal decision thresholds ...
Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
An improved method for expressing the greatest common divisor of n numbers as an integer linear combination of the numbers is presented and analyzed, both theoretically and practi...