The source code and dockerfile for the GSW2024 AI Lab.
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import stormpy
# Knuth's model of a fair die using only fair coins
def example_building_mdps_01():
nr_states = 13
nr_choices = 14
# Transition matrix with custom row grouping: nondeterministic choice over the actions available in states
builder = stormpy.SparseMatrixBuilder(rows=0, columns=0, entries=0, force_dimensions=False,
has_custom_row_grouping=True, row_groups=0)
# New row group, for actions of state 0
builder.new_row_group(0)
builder.add_next_value(0, 1, 0.5)
builder.add_next_value(0, 2, 0.5)
builder.add_next_value(1, 1, 0.2)
builder.add_next_value(1, 2, 0.8)
# State 1
builder.new_row_group(2)
builder.add_next_value(2, 3, 0.5)
builder.add_next_value(2, 4, 0.5)
# State 2
builder.new_row_group(3)
builder.add_next_value(3, 5, 0.5)
builder.add_next_value(3, 6, 0.5)
# State 3
builder.new_row_group(4)
builder.add_next_value(4, 7, 0.5)
builder.add_next_value(4, 1, 0.5)
# State 4
builder.new_row_group(5)
builder.add_next_value(5, 8, 0.5)
builder.add_next_value(5, 9, 0.5)
# State 5
builder.new_row_group(6)
builder.add_next_value(6, 10, 0.5)
builder.add_next_value(6, 11, 0.5)
# State 6
builder.new_row_group(7)
builder.add_next_value(7, 2, 0.5)
builder.add_next_value(7, 12, 0.5)
# Add transitions for the final states
for s in range(8, 14):
builder.new_row_group(s)
builder.add_next_value(s, s - 1, 1)
transition_matrix = builder.build()
# State labeling
state_labeling = stormpy.storage.StateLabeling(nr_states)
# Add labels
labels = {'init', 'one', 'two', 'three', 'four', 'five', 'six', 'done', 'deadlock'}
for label in labels:
state_labeling.add_label(label)
# Set labeling of states
state_labeling.add_label_to_state('init', 0)
state_labeling.add_label_to_state('one', 7)
state_labeling.add_label_to_state('two', 8)
state_labeling.add_label_to_state('three', 9)
state_labeling.add_label_to_state('four', 10)
state_labeling.add_label_to_state('five', 11)
state_labeling.add_label_to_state('six', 12)
# Set label 'done' for multiple states
state_labeling.set_states('done', stormpy.BitVector(nr_states, [7, 8, 9, 10, 11, 12]))
# Choice labeling
choice_labeling = stormpy.storage.ChoiceLabeling(nr_choices)
choice_labels = {'a', 'b'}
# Add labels
for label in choice_labels:
choice_labeling.add_label(label)
# Set labels
choice_labeling.add_label_to_choice('a', 0)
choice_labeling.add_label_to_choice('b', 1)
print(choice_labeling)
# Reward models
reward_models = {}
# Create a vector representing the state-action rewards
action_reward = [0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
reward_models['coin_flips'] = stormpy.SparseRewardModel(optional_state_action_reward_vector=action_reward)
# Collect components
components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling,
reward_models=reward_models, rate_transitions=False)
components.choice_labeling = choice_labeling
# Build the model
mdp = stormpy.storage.SparseMdp(components)
print(mdp)
if __name__ == '__main__':
example_building_mdps_01()