def case_1():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_1.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the pedestrians
targets = []
for i in range(1, 6):
t = lomap.Markov()
t.read_from_file('./target_%d.txt' % i)
targets.append(t)
formula = '! col U end'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
# Classical
with lomap.Timer(
'Classical (non-incremental) Method: Case 1 - Avoid pedestrians'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_1)
pass
# Incremental
with lomap.Timer('Incremental Method: Case 1 - Avoid pedestrians'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets, set_props_1)
def case_1():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_1.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the pedestrians
targets = []
for i in range(1,6):
t = lomap.Markov()
t.read_from_file('./target_%d.txt' % i)
targets.append(t)
formula = '! col U end'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 1 - Avoid pedestrians'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_1)
pass
# Incremental
with lomap.Timer('Incremental Method: Case 1 - Avoid pedestrians'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets, set_props_1)
def case_3b():
# Read the vehicle model
vehicle = lomap.Ts.load('./vehicle_2.yaml')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the guards
targets = []
for i in range(1,7):
t = lomap.Markov.load('./trap_{}.yaml'.format(i))
targets.append(t)
# Reach end safely
formula = '! unsafe U end'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.from_formula(formula)
fsa.add_trap_state()
#fsa.visualize()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 3b - Order 2'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_3)
pass
# Incremental
targets_inc = [targets[2], targets[3], targets[0], targets[1], targets[5],
targets[4]]
with lomap.Timer('Incremental Method: Case 3b - Order 2'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_3)
pass
def case_2b():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_1.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the pedestrians
targets = []
for i in range(1, 6):
t = lomap.Markov()
t.read_from_file('./target_%d.txt' % i)
targets.append(t)
formula = '( F catch0 | F catch1 | F catch2 | F catch3 ) & ( ! col4 U end )'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
# Classical
with lomap.Timer(
'Classical (non-incremental) Method: Case 2b - Save at least one friendly'
):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_2)
pass
# Incremental
targets_inc = [targets[-1]] + targets[:-1]
assumed_props = [('ped0c2', 'ped1c2', 'ped2c2', 'ped3c2'),
('ped1c2', 'ped2c2', 'ped3c2'), ('ped2c2', 'ped3c2'),
('ped3c2'), ()]
with lomap.Timer(
'Incremental Method: Case 2b - Save at least one friendly'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_2,
assumed_props)
pass
def case_2b():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_1.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the pedestrians
targets = []
for i in range(1,6):
t = lomap.Markov()
t.read_from_file('./target_%d.txt' % i)
targets.append(t)
formula = '( F catch0 | F catch1 | F catch2 | F catch3 ) & ( ! col4 U end )'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 2b - Save at least one friendly'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_2)
pass
# Incremental
targets_inc = [targets[-1]] + targets[:-1]
assumed_props = [('ped0c2','ped1c2','ped2c2','ped3c2'),
('ped1c2','ped2c2','ped3c2'),
('ped2c2','ped3c2'),
('ped3c2'),
()]
with lomap.Timer('Incremental Method: Case 2b - Save at least one friendly'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_2, assumed_props)
pass
def case_2a():
# Read the vehicle model
vehicle = lomap.Ts.load('./vehicle_1.yaml')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the pedestrians
targets = []
for i in range(1,6):
t = lomap.Markov.load('./target_{}.yaml'.format(i))
targets.append(t)
formula = 'F catch0 & F catch1 & F catch2 & F catch3 & ( ! col4 U end )'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.from_formula(formula)
fsa.add_trap_state()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 2a - '
'Save all friendlies'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_2)
pass
# Incremental
targets_inc = [targets[-1]] + targets[:-1]
assumed_props = [('ped0c2','ped1c2','ped2c2','ped3c2'),
('ped1c2','ped2c2','ped3c2'),
('ped2c2','ped3c2'),
('ped3c2'),
()]
with lomap.Timer('Incremental Method: Case 2a - Save all friendlies'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_2,
assumed_props)
pass
def case_3b():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_2.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the guards
targets = []
for i in range(1, 7):
t = lomap.Markov()
t.read_from_file('./trap_%d.txt' % i)
targets.append(t)
# Reach end safely
formula = '! unsafe U end'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
#fsa.visualize()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 3b - Order 2'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_3)
pass
# Incremental
targets_inc = [
targets[2], targets[3], targets[0], targets[1], targets[5], targets[4]
]
with lomap.Timer('Incremental Method: Case 3b - Order 2'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_3)
pass
def case_3a():
# Read the vehicle model
vehicle = lomap.Ts()
vehicle.read_from_file('./vehicle_2.txt')
# Convert the vehicle model to an MDP
vehicle_mdp = lomap.Markov()
vehicle_mdp.mdp_from_det_ts(vehicle)
# Read the models of the guards
targets = []
for i in range(1,7):
t = lomap.Markov()
t.read_from_file('./trap_%d.txt' % i)
targets.append(t)
# Reach end safely
formula = '! unsafe U end'
# Construct the full-state fsa using scheck
# (full-state ensures proper MDP after product)
logger.info('Formula: %s' % formula)
fsa = lomap.Fsa()
fsa.fsa_from_cosafe_formula(formula)
fsa.add_trap_state()
#fsa.visualize()
# Classical
with lomap.Timer('Classical (non-incremental) Method: Case 3a - Order 1'):
lomap.classical_synthesis(vehicle_mdp, fsa, targets, set_props_3)
pass
# Incremental
targets_inc = targets
with lomap.Timer('Incremental Method: Case 3a - Order 1'):
lomap.incremental_synthesis(vehicle_mdp, fsa, targets_inc, set_props_3)
pass