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fybazs's Projects

agentgpt icon agentgpt

πŸ€– Assemble, configure, and deploy autonomous AI Agents in your browser.

airsim icon airsim

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

algodeck icon algodeck

An Open-Source Collection of 200+ Flash Cards to Help You Preparing Your Algorithms & Data Structures Interview πŸ’―

algorithms.js icon algorithms.js

Atwood's Law applied to CS101 - Classic algorithms and data structures implemented in JavaScript

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

bluesky icon bluesky

The open source air traffic simulator

c-plus-plus icon c-plus-plus

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

daidalus icon daidalus

open source release: LAR-19282-1 Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) with Dynamic Well-Clear Separation Volumes).

director icon director

A robotics interface and visualization framework, with extensive applications for working with http://drake.mit.edu

dsa-bootcamp-java icon dsa-bootcamp-java

This repository consists of the code samples, assignments, and notes for the Java Data Structures & Algorithms bootcamp of Community Classroom.

flow icon flow

Computational framework for reinforcement learning in traffic control

garage icon garage

A framework for reproducible reinforcement learning research

malmo icon malmo

Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:

mason icon mason

MASON Multiagent Simulation Toolkit

ml-airport-configuration icon ml-airport-configuration

The ML-airport-configuration software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for predicting airport configuration as a time series. The software is designed to point to databases which are not provided as part of the software release and thus

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