text: def __init__(self, name, model, env):        super().__init__(model, env)        self.name = name    def random_action(self):        action = self.env.action_space(self.name).sample()        return actionRock, Paper, Scissorsâ€‹We can now run a simulation of a multi-agent rock, paper, scissors game using the PettingZooAgent.from pettingzoo.classic import rps_v2env = rps_v2.env(max_cycles=3, render_mode="human")agents = {    name: PettingZooAgent(name=name, model=ChatOpenAI(temperature=1), env=env)    for name in env.possible_agents}main(agents, env)        Observation: 3    Reward: 0    Termination: False    Truncation: False    Return: 0                Action: 1        Observation: 3    Reward: 0    Termination: False    Truncation: False    Return: 0                Action: 1        Observation: 1    Reward: 0    Termination: False    Truncation: False    Return: 0                Action: 2        Observation: 1    Reward: 0    Termination: False    Truncation: False    Return: