OpenAI LunarLander-v2 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
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Updated
Aug 11, 2021 - Python
OpenAI LunarLander-v2 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
Implementation of reinforcement learning algorithms for the OpenAI Gym environment LunarLander-v2
Muesli RL algorithm implementation (PyTorch) (LunarLander-v2)
Implement RL algorithms in PyTorch and test on Gym environments.
We apply DQN algorithm to make and artificial agent learn how to land space-craft on moon.
RL with OpenAI Gym
PyTorch application of reinforcement learning algorithm in OpenAI LunarLander - DDPG
Solving OpenAI Gym's Lunar Lander environment using Deep Reinforcement Learning
Teaching to an agent to play the Lunar Lander game from OpenAI Gym using REINFORCE.
reinforcement learning Double Deep Q Learning (DDQN) method to solve OpenAi Gym "LunarLander-v2" by usnig Double Deep NeuralNetworks
LunarLander-v2 learning how to land efficiently using DQN and DDQN for training
Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.
Implementation of reinforcement learning algorithms for the OpenAI Gym environment LunarLander-v2
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
Semester project for the AI Applications class of the MSc in Artificial Intelligence
📖 Paper: Continuous control with deep reinforcement learning 🕹️
Experiment 1: Comparison of key bandit algorithms; Experiment 2: Comparison of Q and SARSA Learning on Taxiv3 environment' ; Experiment 3: Comparison of Q, SARSA and CEM Learning on LunarLanderv2 Environment
This project uses the pytorch package to implement DQN and DDPG models to automate the LunarLander-v2 and LunarLanderContinuous-v2 games.
Deep Q-Network example from Udacity's Deep Reinforcement Learning Nanodegree.
Deep learning and Neural Networks course labs&homeworks&assignments
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