concepts.dm.pdsketch.strips.strips_heuristics.StripsRPGHeuristic#

class StripsRPGHeuristic[source]#

Bases: StripsHeuristic

RPG heuristic (relaxed planning graph).

Methods

`compute`(state)	Compute the heuristic value of the given state.
`compute_rpg_forward_diff`(state[, relaxed_task])	Compute the relaxed planning graph using forward differentiation.
`from_type`(type_identifier, task[, translator])	Create a heuristic from the given type identifier.

Attributes

`goal_func`	The (compiled version) of goal function of the task.
`relaxed`	The relaxed version of the task.
`task`	The grounded STRIPS planning task.
`translator`	The translator used to translate the task representation into the GS* (grounded STRIPS) representation.

__init__(task, translator=None, forward_relevance_analysis=True, backward_relevance_analysis=True)[source]#

Initialize an RPG heuristic.

Parameters:

task (GStripsProblem) – the grounded STRIPS planning task.
translator (GStripsTranslatorBase | None) – the translator used to translate the planning task to the GS* (grounded STRIPS) representation.
forward_relevance_analysis (bool) – whether to perform forward relevance analysis.
backward_relevance_analysis (bool) – whether to perform backward relevance analysis.

compute(state)[source]#

Compute the heuristic value of the given state.

Parameters:: state (SState) – the state to compute the heuristic value.
Returns:: the heuristic value of the given state.
Return type:: int

compute_rpg_forward_diff(state, relaxed_task=None)[source]#

Compute the relaxed planning graph using forward differentiation.

Parameters:

state (SState) – the state to compute the relaxed planning graph.
relaxed_task (GStripsProblem | None) – the relaxed version of the task. If not provided, the task will be relaxed using the translator.

Returns:

a list of sets of states, where each set contains all the states that can be reached from the initial state in the given number of steps.
a dictionary that maps propositions to their level.
a list of lists of tuples, where each tuple contains the following elements:
- the index of the action in the relaxed task operator list.
- the index of the effect in the operator.
- the propositions that contributes to the effect (computed using Forward Diff).
a list of lists of tuples, where each tuple contains the following elements:
- the index of the action that achieves the proposition.
- the level of the proposition.
- the set of propositions that are achieved by the action.
the result of forward differentiation of the goal function.

Return type:

the relaxed planning graph, which is represented as a tuple of the following elements

classmethod from_type(type_identifier, task, translator=None, **kwargs)#

Create a heuristic from the given type identifier.

Parameters:

type_identifier (str) – the type identifier of the heuristic.
task (GStripsProblem) – the grounded STRIPS planning task.
translator (GStripsTranslatorBase | None) – the translator used to translate the planning task to the GS* (grounded STRIPS) representation.
**kwargs – additional arguments to pass to the constructor.

Returns:

the created heuristic.

Return type:

StripsHeuristic

property goal_func: Callable[[SState], bool | GSBoolForwardDiffReturn]#: The (compiled version) of goal function of the task.

property translator: GStripsTranslatorBase | None#: The translator used to translate the task representation into the GS* (grounded STRIPS) representation.