# builders.solver.maskability
Domain specification
# ApplicableActions
A solver must inherit this class if he can use information about applicable action.
This characteristic will be checked during rollout so that retrieve_applicable_actions() will be called before
each call to step(). For instance, this is the case for solvers using action masks (see Maskable).
# retrieve_applicable_actions ApplicableActions
retrieve_applicable_actions(
self,
domain: Domain
) -> None
Retrieve applicable actions and use it for future call to self.step().
To be called during rollout to get the actual applicable actions from the actual domain used in rollout.
# using_applicable_actions ApplicableActions
using_applicable_actions(
self
)
Tell if the solver is able to use applicable actions information.
For instance, action masking could be possible only if considered domain action space is enumerable for each agent.
The default implementation returns always True.
# Maskable
A solver must inherit this class if he can use action masks to sample actions.
For instance, it can be the case for wrappers around RL solvers like sb3_contrib.MaskablePPO or ray.rllib with
custom model making use of action masking.
An action mask is a format for specifying applicable actions when the action space is enumerable and finite. It is
an array with 0's (for non-applicable actions) and 1's (for applicable actions). See Events.get_action_mask() for
more information.
# get_action_mask Maskable
get_action_mask(
self
) -> Optional[StrDict[Mask]]
Retrieve stored action masks.
To be used by self.sample_action().
Returns None if self.set_action_mask() was not called.
# retrieve_applicable_actions ApplicableActions
retrieve_applicable_actions(
self,
domain: Domain
) -> None
Retrieve applicable actions and use it for future call to self.step().
To be called during rollout to get the actual applicable actions from the actual domain used in rollout. Transform applicable actions into an action_mask to be use when sampling action.
# set_action_mask Maskable
set_action_mask(
self,
action_mask: Optional[StrDict[Mask]]
) -> None
Set the action mask.
To be called during rollout before self.sample_action(), assuming that
self.sample_action() knows what to do with it.
Autocastable so that it can use action_mask from original domain during rollout.
# using_applicable_actions ApplicableActions
using_applicable_actions(
self
)
Tell if the solver is able to use applicable actions information.
For instance, action masking could be possible only if considered domain action space is enumerable for each agent.
The default implementation returns always True.
# _set_action_mask Maskable
_set_action_mask(
self,
action_mask: Optional[StrDict[Mask]]
) -> None
Set the action mask.
To be called during rollout before self.sample_action(), assuming that
self.sample_action() knows what to do with it.