This project implements and analyzes the policy gradient (gradient bandit) algorithm for the N-armed Gaussian bandit problem. The bandit environment consists of N=20 arms with true reward values drawn ...

This repository contains implementations of two famous problems in reinforcement learning: Gradient Bandit and Policy Iteration. These problems are fundamental in understanding the principles of ...

Abstract: This article examines an online distributed optimization problem over an unbalanced digraph, in which a group of nodes in the network tries to collectively search for a minimizer of a ...

How does a gambler maximize winnings from a row of slot machines? This is the inspiration for the "multi-armed bandit problem," a common task in reinforcement learning in which "agents" make choices ...

Abstract: This study developed a gradient-based algorithm to synthesize arbitrary power patterns with only element phases. This algorithm does not rely on any general-purpose nonlinear solver and ...

The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult computational problem. Many aspects of modern applied research ...