Function approximation, a central theme in numerical analysis and applied mathematics, seeks to represent complex functions through simpler or more computationally tractable forms. In this context, ...

Abstract: We propose applying the reaction-diffusion equation on a graph to the function approximation for reinforcement learning. which realizes adaptive resolution according to the complexity of the ...

Abstract: Function approximation has experienced significant success in the field of reinforcement learning (RL). Despite a handful of progress on developing theory for nonstationary RL with function ...

Learn how to approximate the integral of a function using the Reimann sum approximation. Reimann sum is an approximation of the area under a curve or between two curves by dividing it into multiple ...

Function Approximation and Classification implementations using Neural Network Toolbox in MATLAB. Function Approximation was done on California Housing data-set and Classification was done on SPAM ...

This project involves approximating a function to solve an optimization problem. Functions can often be costly to write in code. Approximating a function can sometimes save time and money. Especially ...