MultiAgentEnv API



Convert gym.Env into MultiAgentEnv

ray.rllib.env.multi_agent_env.make_multi_agent(env_name_or_creator: Union[str, Callable[[ray.rllib.env.env_context.EnvContext], Any]]) → Type[MultiAgentEnv][source]

Convenience wrapper for any single-agent env to be converted into MA.

Allows you to convert a simple (single-agent) gym.Env class into a MultiAgentEnv class. This function simply stacks n instances of the given `gym.Env` class into one unified MultiAgentEnv class and returns this class, thus pretending the agents act together in the same environment, whereas - under the hood - they live separately from each other in n parallel single-agent envs.

Agent IDs in the resulting and are int numbers starting from 0 (first agent).


env_name_or_creator – String specifier or env_maker function taking an EnvContext object as only arg and returning a gym.Env.


New MultiAgentEnv class to be used as env. The constructor takes a config dict with num_agents key (default=1). The rest of the config dict will be passed on to the underlying single-agent env’s constructor.


>>> # By gym string:
>>> ma_cartpole_cls = make_multi_agent("CartPole-v0")
>>> # Create a 2 agent multi-agent cartpole.
>>> ma_cartpole = ma_cartpole_cls({"num_agents": 2})
>>> obs = ma_cartpole.reset()
>>> print(obs)
... {0: [...], 1: [...]}
>>> # By env-maker callable:
>>> from ray.rllib.examples.env.stateless_cartpole import          ...    StatelessCartPole
>>> ma_stateless_cartpole_cls = make_multi_agent(
...    lambda config: StatelessCartPole(config))
>>> # Create a 3 agent multi-agent stateless cartpole.
>>> ma_stateless_cartpole = ma_stateless_cartpole_cls(
...    {"num_agents": 3})
>>> print(obs)
... {0: [...], 1: [...], 2: [...]}