This project demonstrates the application of Reinforcement Learning (RL) algorithms to control the Hopper environment from the MuJoCo physics simulator. The primary objective is to train an RL agent to learn how to make the simulated hopper move forward efficiently by learning to balance and hop on a single leg.
active 2024-09-27 → 2025-02-26 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 153 days from 2024-09-27 to 2025-02-26. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| stefbarcio | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.