### Installation
```
pip install connect-four-game
```
## Usage
### Human vs Human
```python
from connect_four_game import Game, Agent
if __name__ == '__main__':
red_agent = Agent('RED TEAM', 'red')
blue_agent = Agent('BLUE TEAM', 'blue')
lcm = Game(red_agent, blue_agent)
lcm.start_game()
```
### AI vs AI
```python
from connect_four_game import Game
COLUMN_COUNT = 12 # normally 7
ROW_COUNT = 9 # normally 6
if __name__ == '__main__':
red_rl_agent = RLAgent('red') # RLAgent is not included in the package
blue_rl_agent = RLAgent('blue')
game = Game(red_rl_agent, blue_rl_agent, row_count=ROW_COUNT, column_count=COLUMN_COUNT)
game.start_game()
```
#### Example of an RL Agent which randomly chooses columns
```python
import random
from connect_four_game import BaseAgent
import numpy as np
class RLAgent(BaseAgent):
def __init__(self, color: str, initial_exploration_rate=0.9):
self.name = f'RL-Agent-{color.capitalize()}'
self.color = color
self.symbol = color[0].capitalize()
def choose_action(self):
return random.randint(0, len(self.game.grid[0]) - 1)
def place_block(self):
column = self.choose_action()
return self.board.place_block(column, self.symbol)
def post_evaluation_hook(self):
print('This method is called after each move has been evaluated')
```
### Human vs AI
On the way...
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