The source code and dockerfile for the GSW2024 AI Lab.
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
This repo is archived. You can view files and clone it, but cannot push or open issues/pull-requests.
|
|
import stormpy import stormpy.core import stormpy.simulator
import stormpy.shields
import stormpy.examples import stormpy.examples.files
"""
Example for the extraction of a Post Safety Shield from a model checking result and querying the shield for allowed actions.
"""
def post_shield_extraction(): path = stormpy.examples.files.prism_mdp_lava_simple formula_str = "Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
program = stormpy.parse_prism_program(path) formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
options = stormpy.BuilderOptions([p.raw_formula for p in formulas]) options.set_build_state_valuations(True) options.set_build_choice_labels(True) options.set_build_all_labels() model = stormpy.build_sparse_model_with_options(program, options)
initial_state = model.initial_states[0] assert initial_state == 0 shield_specification = stormpy.logic.ShieldExpression(stormpy.logic.ShieldingType.POST_SAFETY, stormpy.logic.ShieldComparison.RELATIVE, 0.9) result = stormpy.model_checking(model, formulas[0], extract_scheduler=True, shield_expression=shield_specification) assert result.has_scheduler assert result.has_shield shield = result.shield post_scheduler = shield.construct() for state_id in model.states: choices = post_scheduler.get_choice(state_id) print(F"Applied corrections in state {state_id}, are {choices.choice_map} ")
if __name__ == '__main__': post_shield_extraction()
|