Research internship during the 5th semester of my B.Sc CBT degree @ TUM CS
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Updated
Jul 4, 2023 - Python
Research internship during the 5th semester of my B.Sc CBT degree @ TUM CS
Self-solving control problems from OpenAI Gym with NEAT
This repository contains a re-implementation of the Proximal Policy Optimization (PPO) algorithm, originally sourced from Stable-Baselines3.
Useless try to create neural network
Deep Q-Learning algorithms to solve LunarLander-v2.
Semester project for the AI Applications class of the MSc in Artificial Intelligence
📖 Paper: Continuous control with deep reinforcement learning 🕹️
This project uses the pytorch package to implement DQN and DDPG models to automate the LunarLander-v2 and LunarLanderContinuous-v2 games.
Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.
PyTorch application of reinforcement learning algorithm in OpenAI LunarLander - DDPG
Solving OpenAI Gym's Lunar Lander environment using Deep Reinforcement Learning
Implement RL algorithms in PyTorch and test on Gym environments.
Implementation of reinforcement learning algorithms for the OpenAI Gym environment LunarLander-v2
OpenAI LunarLander-v2 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
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