Board Game Models
AlphaZero
Introduced by Silver et al. in Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning AlgorithmAlphaZero is a reinforcement learning agent for playing board games such as Go, chess, and shogi.
Source: Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Board Games | 12 | 30.00% |
| Atari Games | 6 | 15.00% |
| Game of Go | 5 | 12.50% |
| Decision Making | 4 | 10.00% |
| Game of Chess | 3 | 7.50% |
| Game of Shogi | 2 | 5.00% |
| Automated Theorem Proving | 1 | 2.50% |
| Incremental Learning | 1 | 2.50% |
| Model-based Reinforcement Learning | 1 | 2.50% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
