Reinforcement learning tutorials

This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.

Multi agent gym environment based on the classic Snake game with implementations of various reinforcement learning algorithms in pytorch

Developed a highly customizable OpenAI gym environment and trained a stable_baselines3 PPO agent. Used the expert agent for Imitation Learning with DAgger

State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping

A deep reinforcement learning Bot for https://kana.byha.top:444/

Modular Reinforcement Learning in PyTorch.

AI agent learns to walk, run, hop and crawl with out any given data using proximal policy optimisation.

MIMARI 9.0 is not a technical analysis bot; it is a mathematical framework that models financial markets as noisy, regime-switching, jump-diffusion, and quantum-like probability distributions.

Reinforcement learning(PPO) for 2D Car

Repository for the final project of the "Computational Intelligence" course @ PoliTo, 2022/2023

无人机自主溯源甲烷羽流系统/Autonomous UAV Methane Plume Tracing System

This project integrates MicroK8s (lightweight Kubernetes) with Reinforcement Learning (RL) for adaptive autoscaling compared to traditional solutions (HPA/CA).

The aim of this repository is the analysis and study of computer intelligence and in-depth learning techniques in the development of intelligent gaming agents.

Short own implementation of the game snake. In this project I'am using the ray library together with ray tune and a custom PPO model.

Personal project - attempting to train an RL model to trade crypto/other markets

A Deep Reinforcement Learning (DRL) solution for the Job Scheduling Problem using PPO and Stable Baselines3. Optimized to minimize makespan by balancing workloads across machines in a custom OpenAI Gym environment, outperforming standard heuristic baselines.

An RL agent that finds an optimal policy of cleaning dirt off a floor with a power washer.

Sample implementation of gridworld problem in pygame with dynamic obstacles using Q-learning and PPO algorithm

Unleashing the Power of PPO: Mastering Super Mario with Reinforcement Learning. Dive into our journey of training a Proximal Policy Optimization (PPO) agent to conquer the classic NES.