The source code and dockerfile for the GSW2024 AI Lab.
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import stormpy import stormpy.core import stormpy.simulator
import stormpy.shields
import stormpy.examples import stormpy.examples.files
def optimal_shield_extraction(): path = stormpy.examples.files.prism_smg_robot formula_str = "<Optimal> <<sh>> R{\"travel_costs\"}min=? [ LRA ]"
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) shield_specification = stormpy.logic.ShieldExpression(stormpy.logic.ShieldingType.OPTIMAL) 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
state_ids = [x for x in model.states] scheduler = shield.construct()
for state_id in state_ids[0:50]: choices = scheduler.get_choice(state_id) print(F"Corrections in state {state_id}, are {choices.choice_map} ")
if __name__ == '__main__': optimal_shield_extraction()
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