Reda Elmarhouch's Projects
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
Algorithm applied to solve three-tiered optimization problem of UGV and UAV routing. This is a part of our research work https://rdcu.be/cVNpM published in Journal of Intelligent and Robotic Systems (JINT).
Emily, Jon and Zane's 221 final project
Paper list of multi-agent reinforcement learning (MARL)
This is just a simple API tracker for covid-19 latest information for eleminated, recovered, confirmed and deaths cases in morocco. you can try it here
This Repository is for A first Moroccan Stock Market API
This project implements various multi-agent coordination techniques.
A leader-follower formation control using deep reinforcement learning environment, In which every agent can learn to follow the leader agent by keeping track of a certain distance to that leader, avoiding obstacles, and avoiding collision with the other agents.
UAV Flight Simulator Gymnasium Environments
Boids simulation using Python and Pyglet
(in development). Implementation of Neural Dyna Q-Learning. See abstract in README file.
(Complete). An open-architecture multi-agent quadcopter simulator. We implement a few modern techniques for improving the performance of aerial vehicles, including reinforcement learning and shifting planar inequalities for obstacle avoidance.
development of a rasa chatbot on google colab
POC: Starter-pack for Insurance Bot with Rasa and Rasa X.
Personal experiments on Reinforcement Learning
This contains assignments of the Robotics course
(In development). This project implements shepherding for a group of dynamic agents.
The Moroccan Stock Market Tracker, a dashboard using a REST api to get the latest data from the Moroccan Stock Market Directly from Casablanca Stock Market.
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
What I Know And What I Need To Learn