def default_specs():
"""Define specs for simulation of SS-2
m = 3
"""
specs = MyInputs2()
# load graph, either by number (int), iGraph object or .p file name (str)
specs.set_graph(8)
# solver parameter: central x distributed
specs.set_solver_type('distributed')
# target motion
specs.set_target_motion('static')
# searchers' detection: capture range and false negatives
m = 3
specs.set_capture_range(0)
specs.set_size_team(m)
# time-step stuff: deadline mission (tau), planning horizon (h), re-plan frequency (theta)
h = 5
specs.set_all_times(h)
specs.set_theta(1)
# solver timeout (in sec)
specs.set_timeout(10)
specs.use_default()
# danger stuff (uncomment to change)
# specs.set_threshold(value, 'kappa')
# specs.set_threshold(value, 'alpha')
# specs.set_danger_data(eta_priori, eta_check)
return specs
def get_believes():
specs = specs_num_sim()
for turn in specs.list_turns:
# set seed according to run #
specs.set_seeds(turn)
# set new belief
n = 46
b0 = MyInputs2.pick_random_belief(n, specs.target_seed)
# print(b0)
if turn > 30:
break
def get_specs_prob():
specs = MyInputs2()
# test graph
specs.set_graph(4)
# solver parameter: central x distributed
specs.set_solver_type('distributed')
# target motion
specs.set_target_motion('static')
# searchers' detection: capture range and false negatives
m = 2
specs.set_capture_range(0)
specs.set_size_team(m)
# position
v0 = [1, 1]
specs.set_start_searchers(v0)
b_0 = [0.0 for i in range(10)]
b_0[8] = 0.5
b_0[6] = 0.5
specs.set_b0(b_0)
# time-step stuff: deadline mission (tau), planning horizon (h), re-plan frequency (theta)
h = 3
specs.set_all_times(h)
specs.set_theta(1)
# solver timeout (in sec)
specs.set_timeout(10)
# danger stuff
specs.set_threshold([3, 4], 'kappa')
specs.set_danger_perception('prob')
specs.set_threshold([0.9, 0.9], 'alpha')
eta_true = [1, 3, 3, 4, 5, 3, 4, 4, 1]
# transform in distribution
eta_priori = []
for level in eta_true:
eta = MyDanger.eta_from_z(level, 1)
eta_priori.append(eta)
specs.set_danger_data(eta_true, 'true')
specs.set_danger_data(eta_priori, 'priori')
return specs
def get_specs():
specs = MyInputs2()
specs.set_graph(4)
# solver parameter: central x distributed
specs.set_solver_type('distributed')
# target motion
specs.set_target_motion('static')
# searchers' detection: capture range and false negatives
m = 2
specs.set_capture_range(0)
specs.set_size_team(m)
# position
v0 = [1, 1]
specs.set_start_searchers(v0)
b_0 = [0.0 for i in range(10)]
b_0[8] = 0.5
b_0[6] = 0.5
specs.set_b0(b_0)
# time-step stuff: deadline mission (tau), planning horizon (h), re-plan frequency (theta)
h = 3
specs.set_all_times(h)
# specs.set_theta(3)
# solver timeout (in sec)
specs.set_timeout(10)
# danger stuff
specs.set_threshold([3, 4], 'kappa')
eta_true = [1, 3, 3, 4, 5, 3, 4, 4, 1]
eta_priori = eta_true
specs.set_danger_data(eta_true, 'true')
specs.set_danger_data(eta_priori, 'priori')
return specs
def specs_basic():
# initialize default inputs
specs = MyInputs2()
# ------------------------
# graph number -- SS-2: 8
specs.set_graph(8)
# solver parameter: central x distributed
specs.set_solver_type('distributed')
# solver timeout (in seconds)
specs.set_timeout(10)
# ------------------------
# time stuff: deadline mission (tau), planning horizon (h), re-plan frequency (theta)
specs.set_horizon(14)
specs.set_deadline(100)
specs.set_theta(1)
specs.set_capture_range(0)
specs.set_zeta(None)
# ------------------------
# target motion
specs.set_target_motion('static')
specs.set_start_target_vertex(None)
return specs