malib.rollout.envs.gym package

malib.rollout.envs.gym.env_desc_gen(**config)

Submodules

malib.rollout.envs.gym.env module

class malib.rollout.envs.gym.env.GymEnv(**configs)

Bases: Environment

Single agent gym envrionment

property action_spaces: Dict[str, Space]

A dict of agent action spaces

close()

property observation_spaces: Dict[str, Space]

A dict of agent observation spaces

property possible_agents: List[str]

Return a list of environment agent ids

render(*args, **kwargs)

reset(max_step: Optional[int] = None)

Reset environment and the episode info handler here.

time_step(actions: Dict[str, Any]) → Tuple[Dict[str, Any], Dict[str, float], Dict[str, bool], Dict[str, Any]]

Environment stepping logic.

Parameters:

actions (Dict[AgentID, Any]) – Agent action dict.

Raises:

NotImplementedError – Not implmeneted error

Returns:

A 4-tuples, listed as (observations, rewards, dones, infos)

Return type:

Tuple[Dict[AgentID, Any], Dict[AgentID, float], Dict[AgentID, bool], Dict[AgentID, Any]]