Abstract: In this paper we propose a novel distributed gradient-based two-time-scale algorithm for multi-agent off-policy learning of linear approximation of the optimal action-value function ...

This article studies the accuracy of two versions of Kydland and Prescott's (1980, 1982) procedure for approximating optimal decision rules in problems in which the objective fails to be quadratic and ...

Ruben (1966) has suggested a simple approximate normalization for the correlation coefficient in normal samples, by representing it as the ratio of a linear combination of a standard normal variable ...

This repository contains the implementation of a linear regression model designed to approximate an unknown function based on available data. The goal is to find a polynomial function that best fits ...