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LunarLander-v2
viswa752/LunarLander-v2
LunarLander-v2 is a reinforcement learning model from viswa752. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
This repository contains my Proximal Policy Optimization (PPO) agent trained using PyTorch and Gymnasium on the LunarLander-v2 environment.
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Public
Updated Sep 14, 2026
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.pt43.3 KB · 91%
At a glance
- Task
- Reinforcement Learning
- Library
- pytorch
- Access
- Public
- Created
- Sep 14, 2026
- Updated
- Sep 14, 2026
- SHA
- c1258d43
Model card
From the Hugging Face model README
PPO LunarLander-v2
This repository contains my Proximal Policy Optimization (PPO) agent trained using PyTorch and Gymnasium on the LunarLander-v2 environment.
Algorithm
The agent uses Proximal Policy Optimization (PPO).
The implementation includes:
- Actor-Critic architecture
- Generalized Advantage Estimation (GAE)
- PPO clipped policy objective
- Clipped value loss
- Advantage normalization
- Entropy regularization
- Gradient clipping
- Learning-rate annealing
Training Details
| Parameter | Value |
|---|---|
| Environment | LunarLander-v2 |
| Algorithm | PPO |
| Total timesteps | 100000 |
| Learning rate | 0.00025 |
| Number of environments | 8 |
| Steps per rollout | 128 |
| Gamma | 0.99 |
| GAE Lambda | 0.95 |
| Minibatches | 4 |
| Update epochs | 4 |
| PPO clip coefficient | 0.2 |
| Entropy coefficient | 0.01 |
| Value coefficient | 0.5 |
| Seed | 1 |
Evaluation
The trained agent was evaluated for 10 episodes.
- Mean reward: -167.32
- Standard deviation: 88.93
Model Architecture
The policy uses an Actor-Critic architecture.
The actor predicts action logits for the discrete LunarLander action space.
The critic estimates the value of the current state.
Both networks contain two fully connected hidden layers with 64 units and Tanh activation functions.
Files
model.pt— trained PyTorch modelhyperparameters.txt— PPO hyperparametersevaluation.txt— evaluation resultsREADME.md— model card
Frameworks
- PyTorch
- Gymnasium
- NumPy
- Task
- Reinforcement Learning
- Library
- pytorch
- Created
- Sep 14, 2026
- Updated
- Sep 14, 2026