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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.
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.
Developed a highly customizable OpenAI gym environment and trained a stable_baselines3 PPO agent. Used the expert agent for Imitation Learning with DAgger
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.
This repository contains the code for a project paper for a Master's module in the field of reinforcement learning. The aim of the project is to explore and implement Proximal Policy Optimization (PPO) agents to learn and play the 7x7 Hex game.