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)
RL with OpenAI Gym
Muesli RL algorithm implementation (PyTorch) (LunarLander-v2)
Implementation of reinforcement learning algorithms for the OpenAI Gym environment LunarLander-v2
Solving OpenAI Gym's Lunar Lander environment using Deep Reinforcement Learning
Implement RL algorithms in PyTorch and test on Gym environments.
PyTorch application of reinforcement learning algorithm in OpenAI LunarLander - DDPG
Teaching to an agent to play the Lunar Lander game from OpenAI Gym using REINFORCE.
Deep RL based solution of LunarLander-v2 environment.
We apply DQN algorithm to make and artificial agent learn how to land space-craft on moon.
Deep learning and Neural Networks course labs&homeworks&assignments
Deep Q-Learning algorithms to solve LunarLander-v2.
Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.
This is a project of reinforcement learning which contains two different environments. The first environment is the taxi driver problem in 4x4 space with the simple Q-learning update rule. In this task, we compared the performance of the e-greedy policy and Boltzmann policy. As a second environment, we chose the LunarLander from the open gym. Fo…
Implementation of reinforcement learning algorithms for the OpenAI Gym environment LunarLander-v2
LunarLander-v2 learning how to land efficiently using DQN and DDQN for training
This repository showcases the implementation of a PPO Clip first-order method to solve the LunarLander discrete environment
Deep Q-Network example from Udacity's Deep Reinforcement Learning Nanodegree.
Behaviour Cloning On OpenAI Environment
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
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