Self-Driving Car Reinforcement Learning 🚘🤔🧠
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Updated
Jun 23, 2024 - Python
Self-Driving Car Reinforcement Learning 🚘🤔🧠
This repository explores the application of three reinforcement learning algorithms—Deep Q-Networks (DQN), Double Deep Q-Networks (DDQN), and Proximal Policy Optimization (PPO)—for playing Super Mario Bros using the OpenAI Gym and nes-py emulator. It includes a comparative analysis of these models.
AI Models for Playing Super Mario Bros
Implementation and performance evaluation of the Bayesian-Expected-Sarsa algorithm in the context of Atari game environment
📖 Paper: Deep Reinforcement Learning with Double Q-learning 🕹️
Reinforcement learning algorithms in poker games
Jaxplorer is a Jax reinforcement learning (RL) framework for exploring new ideas.
Implementation of the Double Deep Q-Learning algorithm with a prioritized experience replay memory to train an agent to play the minichess variante Gardner Chess
Totally Asymmetric Simple Exclusion Process (TASEP) using reinforcement learning (RL) agents
A complete MataLab laboratory for training and evaluating EMG HGR RL DQN and DDQN models.
Genetic algorithm to select the weights of a MLP to play lunar lander using Reinforcement Learning.
reinforcement learning Double Deep Q Learning (DDQN) method to solve OpenAi Gym "LunarLander-v2" by usnig Double Deep NeuralNetworks
This code is the result of the collaboration of RL Turkey team.
Autonomous Driving W/ Deep Reinforcement Learning in Lane Keeping - DDQN and SAC with kinematics/birdview-images
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
controlling an inverted pendulum using DQN , DDQN and PID controller in gym environment.
Naive implementations of deep reinforcement learning algorithms
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