Exploring Lunarlander V2
Let's dive into the details surrounding Lunarlander V2.
- This is a video recording the progression of my Deep Q-Network Agent on the
- Reinforcement Learning (vanilla policy gradients) to land on the Moon.
- Solving the Gym environment
- Solution for the
- 3 layer Neural Network that learned to land space craft on surface with reduced fuel consumption through reinforcement learning ...
In-Depth Information on Lunarlander V2
Timecodes: 0:00 Introduction 0:25 Code overview 1:08 Solution explanation 5:52 Conclusion. Solved with Deep Reinforcement Learning (DQN) in 1000 episodes. Solving OpenAI's Useful Videos - Local Network vs Target Network - https://youtu.be/FhGq_GNicIM Exploration-Exploitation Tradeoff ...
DQN Baseline hyperaparameters. DQN hyperparameters tuned by CMA-ES.
That wraps up our extensive overview of Lunarlander V2.
