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Description:
connectfourgame 0.1.6
Installation
pip install connect-four-game
Usage
Human vs Human
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
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
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...
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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