Up to date progress of Microsoft AirSim from my academic internship. This is a guide on how to get Stable Baseline's reinforcement learning to work alongside the AirSim package with Unreal Engine 4.
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Updated
Jun 8, 2021
Up to date progress of Microsoft AirSim from my academic internship. This is a guide on how to get Stable Baseline's reinforcement learning to work alongside the AirSim package with Unreal Engine 4.
Clean and flexible implementation of PPO (built on top of stable-baselines3)
Simple Training and Evaluation of Multi-Agent Environments with Deep Reinforcement Algorithms 🐨
My Introduction to Evolutionary and Reinforcement Learning
Train Soft Actor-Critic model for KukaDiverseObject environment in pybullet
Source code for the numerical experiments presented in the paper "On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks".
A reinforcement lerning application for selfdriving cars using openai's gym, stablebaselines3 and Microsoft AirSim.
Deep RL framework for exploring state spaces of finite state machines.
Training examples for the Rocket League Gym using Stable-Baselines3
Uses the Stable Baselines 3 and OpenAI Python libraries to train models that attempt to solve the CartPole problem using 3 reinforcement learning algorithms; PPO (Proximal Policy Optimization), A2C (Advantage Actor Critic) and DQN (Deep Q Learning).
OpenAI Gym environment designed for training RL agents to control the flight of a two-dimensional drone.
OpenAI Gym environment designed for training RL agents to bring CartPole upright and its further balancing.
OpenAI Gym environment designed for training RL agents to balance double CartPole.
Implementation of RL algorithms using the stable baselines library
OpenAI Gym environment solutions using Deep Reinforcement Learning.
A custom OpenAI gym environment for training Tic-Tac-Toe agents with Stable-Baselines3
reinforcement learning with wordle and open-ai gym
Game/Simulation which is a 2D-analog of Counter Strike as a target for Deep Reinforcement Learning.
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