CSE 571 Artificial Intelligence

Reinforcement learning algorithms

Easy21 assignment from David Silver's RL Course at UCL

A library of reinforcement learning (RL) algorithms.

X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning

Local function approximation (LFA) framework, NeurIPS 2022

This project is a simple animation of Fourier series, approximating a function using a sum of sine and cosine functions.

An implementation of multilayer perceptron(MLP) on function approximation.

Practical experiments on Machine Learning in Python. Processing of sentences and finding relevant ones, approximation of function with polynomials, function optimization

A short and sweet library handling uncertainty in calculations. Can use both standard, probabilistic uncertainties and maximal uncertainties for arbitrary functions over arbitrary variables.

A generic implementation of multi layer perceptron neural networks, including some visual tools. Contains example of using the neural network classes for function approximation.

Many different Neural Networks in Python Language. This repository is an independent work, it is related to my 'Redes Neuronales' repo, but here I'll use only Python.

This repository contains numerical methods for finding solutions of a nonlinear equation as well as to approximate functions from a dataset of (x, y) points.

In this university project, genetic programming is used to approximate the function

The efficient alternative to Neural Networks. Implements SLRM (Segmented Linear Regression Model) for neural compression and non-linear data modeling, achieving high precision with a fraction of the parameters of a traditional ANN.

A data driven model using RL to solve a traffic simulation optimization problem to minimize cars’ carbon emissions.

Dash App for visualizing function approximations by polynomials.

Estimation of a non-linear function using neural networks