Go AI Reinforcement Learning Project - This repository is dedicated to exploring and comparing two reinforcement learning methods—gradient descent and Q-value learning—in developing intelligent agents for the board game Go. The goal is to observe the model’s evolution after generating thousands of self-played games and compare agents’ results.
active 2023-10-30 → 2024-10-25 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 362 days from 2023-10-30 to 2024-10-25. Pushes: 26 total, peak 4 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
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- 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 |
|---|---|---|---|---|
| DariMe20 | 26 | 26 | 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.