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()