Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function ...

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This paper presents two sets of considerations on the use of approximations to estimate freight trip generation (FTG) and freight generation (FG) rates, based on a single variable. Following recent ...

This is a program for creating linear and nonlinear approximations of functions. This program was developed in Python using a set of PyQt5 libraries to create a graphical interface. Linear ...

An illustration of a magnifying glass. An illustration of a magnifying glass.

This note describes a rational approximation for the error function which has been found useful in a subroutine as an asymptotic expression of improved accuracy ...

Many types of economic problems require that we consider two variables at the same time. A typical example is the relation between price of a commodity and the demand or supply of that commodity. The ...

In recent years, neural networks have once again triggered an increased interest among researchers in the machine learning community. So-called deep neural networks model functions using a composition ...