Othello game prepared for reinforcement learning with following agents implemented:
- Value Iteration
- MCTS
- SARSA
- SARSA-Lambda
- Expected SARSA
- Q-Learning
- Double Q-Learning
- Value Function Approximation
- Random
Inside src directory: python reversi.py --help:
Usage: reversi.py [OPTIONS] [[human|random|value_iter|mcts|sarsa|exp_sarsa|sar
sa_lambda|q_learning|dq_learning|value_approx]] [[human|rand
om|value_iter|mcts|sarsa|exp_sarsa|sarsa_lambda|q_learning|d
q_learning|value_approx]]
Runs Reversi game of given size, given number of times, with selected
players, which are learning or not, with or without GUI and returns wins
count
Options:
-l1 Enable learning for first player
-l2 Enable learning for second player
-s, --size INTEGER... Size of the map
-n, --number INTEGER Number of game repeats
-d, --delay FLOAT Minimum delay between player moves in ms
--live / --prepared Whether use live or prepared backend
--gui / --nogui Whether graphical interface should be shown
--help Show this message and exit.
Backend specifies how possible player moves, terminal states, subsequent game states are calculated. There are two backends implemented:
- Live - Everything is calculated on the fly, what is relatively slow.
- Prepared - All states, transitions and so on are calculated only once, saved in a file and are fast loaded in subsequent program launches. Require initial delay to build everything, but following games are much faster.
Percent results of 1000 games with random player
| Algorithm | win / lost / draw |
|---|---|
| dq_learning | 98.8 / 0.7 / 0.5 |
| exp_sarsa | 98.3 / 1.4 / 0.3 |
| mcts | 79.3 / 15.8 / 4.9 |
| q_learning | 99.7 / 0.3 / 0.0 |
| sarsa | 99.6 / 0.4 / 0.0 |
| sarsa_lambda | 99.7 / 0.2 / 0.1 |
| value_approx | 93.3 / 6.1 / 0.6 |
| value_iter | 99.5 / 0.3 / 0.2 |
| Algorithm | win / lost / draw |
|---|---|
| dq_learning | 55.6 / 44.3 / 0.1 |
| exp_sarsa | 61.8 / 38.0 / 0.2 |
| mcts | 65.1 / 34.9 / 0.0 |
| q_learning | 59.0 / 40.7 / 0.3 |
| sarsa | 58.2 / 41.5 / 0.3 |
| sarsa_lambda | 92.3 / 7.6 / 0.1 |
| value_approx | 89.4 / 10.5 / 0.1 |
| Algorithm | win / lost / draw |
|---|---|
| value_approx | 79.3 / 18.0 / 2.7 |
| mcts | 47.7 / 46.3 / 6.0 |
| Algorithm | win / lost / draw |
|---|---|
| value_approx | 85.1 / 12.1 / 2.8 |
| sarsa_lambda | 49.9 / 46.1 / 4.0 |
| q_learning | 49.8 / 46.6 / 3.6 |
| mcts | 51.0 / 45.5 / 3.5 |
- Python version:
3.10.5 - Installing requirements:
pip install -r requirements.txt
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