- Step1: Install the package via pip: pip install beer-game-env
- Step2: Import the environment: from beer_game_env import BeerGameEnv
- Step3: Instantiate the environment: env = BeerGameEnv()
- Step4: Use standard Gym loop: obs = env.reset(), action = agent.predict(obs), obs, reward, done, info = env.step(action)
- Step5: Train or evaluate agents using any Gym-compatible RL framework