Mastermind player and learning algorithms by reinforcement learning.
This benchmark is done for a 6 color (or digits) master mind game. The learning is constrained to use 16GB of ram and a max execution time of 1 hour. This is not very rigorous as the execution context is not strictly the same. The last column shows the number of episodes that was possible to fit within these constraints.
| Algorithm | Parameter | Rewards sum of playing 1M games | Episodes |
|---|---|---|---|
| MC epsilon greedy | 0.3 | -690083 | 6M |
| MC epsilon greedy | 0.2 | -286215 | 7M |
| MC epsilon greedy | 0.1 | 848485 | 12M |
| MC epsilon greedy | 0.05 | 1935992 | 22M |
| MC epsilon greedy | 0.01 | 2595339 | 90M |
| MC epsilon greedy | 0 | -936267 | 150M |
| MC exploring starts | - | -908847 | 6M |