sinergym.utils.wrappers.MultiObjectiveReward

class sinergym.utils.wrappers.MultiObjectiveReward(env: Any, reward_terms: List[str])
__init__(env: Any, reward_terms: List[str])

The environment will return a reward vector of each objective instead of a scalar value.

Parameters:
  • env (Any) – Original Sinergym environment.

  • reward_terms (List[str]) – List of keys in reward terms which will be included in reward vector.

Methods

__init__(env, reward_terms)

The environment will return a reward vector of each objective instead of a scalar value.

class_name()

Returns the class name of the wrapper.

close()

Closes the wrapper and env.

get_wrapper_attr(name)

Gets an attribute from the wrapper and lower environments if name doesn't exist in this object.

render()

Uses the render() of the env that can be overwritten to change the returned data.

reset(*[, seed, options])

Uses the reset() of the env that can be overwritten to change the returned data.

step(action)

Perform the action and environment return reward vector.

wrapper_spec(**kwargs)

Generates a WrapperSpec for the wrappers.

Attributes

action_space

Return the Env action_space unless overwritten then the wrapper action_space is used.

metadata

Returns the Env metadata.

np_random

Returns the Env np_random attribute.

observation_space

Return the Env observation_space unless overwritten then the wrapper observation_space is used.

render_mode

Returns the Env render_mode.

reward_range

Return the Env reward_range unless overwritten then the wrapper reward_range is used.

spec

Returns the Env spec attribute with the WrapperSpec if the wrapper inherits from EzPickle.

unwrapped

Returns the base environment of the wrapper.

step(action: int | ndarray) Tuple[ndarray, List[float], bool, bool, Dict[str, Any]]

Perform the action and environment return reward vector.

Parameters:

action (Union[int, np.ndarray]) – Action to be executed in environment.

Returns:

observation, vector reward, terminated, truncated and info.

Return type:

Tuple[ np.ndarray, List[float], bool, bool, Dict[str, Any]]