sinergym.utils.wrappers.MultiObjectiveReward

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

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

Parameters:
  • env (EplusEnv) – 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.

has_wrapper_attr(name)

Checks if the given attribute is within the wrapper or its environment.

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.

set_wrapper_attr(name, value)

Sets an attribute on this wrapper or lower environment if name is already defined.

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.

logger

metadata

Returns the Env metadata.

np_random

Returns the Env np_random attribute.

np_random_seed

Returns the base environment's np_random_seed.

observation_space

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

render_mode

Returns the Env render_mode.

spec

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

unwrapped

Returns the base environment of the wrapper.

logger = <Logger WRAPPER MultiObjectiveReward (INFO)>
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]]