Using deep reinforcement learning to play Snake game. The used algorithm is PPO for discrete! It has the brilliant performance in the field of discrete action space just like in continuous action space. You just need half an hour to train the snake and then it can be as smart as you.|使用深度强化学习玩蛇游戏。 使用的算法是离散的 PPO！ 它在离散动作空间领域有着与连续动作空间一样的出色表现。
active 2023-10-04 → 2024-10-14 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 377 days from 2023-10-04 to 2024-10-14. Pushes: 32 total, peak 8 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 10 total, peak 6 in a day. Comments: 1 total, peak 1 in a day. Stars: 5 total, peak 2 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 |
|---|---|---|---|---|
| MuGeminorum | 17 | 11 | 0 | 0 |
| monet-joe | 17 | 12 | 0 | 1 |
| monetjoe | 9 | 9 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 5 stars here means stars gained during the window, not the repo's star count.