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UnremovableReasoningShurtcuts.py
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UnremovableReasoningShurtcuts.py
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import sys
from itertools import product
import datetime
def find_reasoning_shurtcuts(phi, max_iter, criterion= "acceptance", pruning_maps = True):
#Criterion may be one between:
# "acceptance" = wether traces remain accepted after the symbols modifications
# "reward" = if the traces receive or not the same reward after symbol modifications
# phi = Moore Machine
#TODO: calculate max_iter
if pruning_maps:
iter = 1
else:
iter = max_iter
alphas = set(product(phi.alphabet, repeat= len(phi.alphabet)))
data = set(product(phi.alphabet, repeat = iter))
#print(alphas)
start_time = datetime.datetime.now()
while iter <= max_iter:
print("#### Iteration ", iter)
print("number of maps = {}".format( len(alphas)))
print("number of traces = {}".format(len(data)))
alphas_for = alphas.copy()
for alpha in alphas_for:
survive = check_alpha(data, alpha, phi, criterion)
if not survive:
alphas.remove(alpha)
iter += 1
data = set(product(phi.alphabet, repeat = iter))
end_time = datetime.datetime.now()
time_diff = (end_time - start_time)
execution_time = time_diff.total_seconds()
return alphas, execution_time
def check_alpha(dataset, alpha, phi, criterion):
for trace in dataset:
trace = list(trace)
trace_alpha = substitute_map(trace,alpha)
if criterion == "acceptance":
result_t = phi.accepts(trace)
result_t_a = phi.accepts(trace_alpha)
elif criterion == "reward":
_, result_t = phi.process_trace(trace)
_, result_t_a = phi.process_trace(trace_alpha)
else:
sys.exception("unrecognized criterion for counting RS: {}".format(criterion) )
if result_t != result_t_a:
return False
return True
def substitute_map(trace, alpha):
#trace = str(trace)
#print(trace)
#print(alpha)
return list(map(lambda item: alpha[item], trace))
#print("new trace: ", trace)
#for i, rep in enumerate(alpha):
# trace = trace.replace(i, rep)
# print(trace)
#test
#find_reasoning_shurtcuts("phi", [0,1,2,3,4])
'''
def find_reasoning_shortcuts_NEW(phi):
# phi = Moore Machine
alphas = set(product(phi.alphabet, repeat= len(phi.alphabet)))
D = {}
for alpha in alphas:
D[alpha] = phi.alphabet.copy()
#print(D)
empty_key = (D.keys() == [])
while not empty_key:
next_D = {}
for alpha in D.keys().copy():
if check_alpha(D[alpha], alpha, phi, "acceptance"):
'''
def find_reasoning_shortcuts_NEW(phi):
start_time = datetime.datetime.now()
if -100 in phi.rewards:
terminal_rew = -100
else:
terminal_rew = 100
print("TERMINAL REWARD:", terminal_rew)
one_step_traces = [[p] for p in phi.alphabet]
alphas = set(product(phi.alphabet, repeat= len(phi.alphabet)))
D = {alpha: one_step_traces.copy() for alpha in alphas}
while D:
next_D = {}
for alpha in list(D.keys()):
D_next_alpha = []
if check_alpha(D[alpha], alpha, phi, "acceptance"):
# Expand dataset for the next iteration
# Check terminal states
for t in D[alpha]:
t_a = substitute_map(t, alpha)
t_state, t_rew = phi.process_trace(t)
t_a_state, t_a_rew = phi.process_trace(t_a)
t_state_terminal = (t_rew == terminal_rew)
t_a_state_terminal = (t_a_rew == terminal_rew)
if not t_state_terminal or not t_a_state_terminal:
# Check dummy transitions
for p in phi.alphabet:
t_prime = t + [p]
t_pr_state, _ = phi.process_trace(t_prime)
t_pr_a = substitute_map(t_prime, alpha)
t_pr_a_state, _ = phi.process_trace(t_pr_a)
if t_state != t_pr_state or t_a_state != t_pr_a_state:
D_next_alpha.append(t_prime)
else:
del D[alpha]
if D_next_alpha:
next_D[alpha] = D_next_alpha
reasoning_shortcuts = set(D.keys())
D = next_D
end_time = datetime.datetime.now()
time_diff = (end_time - start_time)
execution_time = time_diff.total_seconds()
return reasoning_shortcuts, execution_time
from ltlf2dfa.parser.ltlf import LTLfParser
def find_reasoning_shortcuts_naif(phi, alphabet ):
start_time = datetime.datetime.now()
#put the declare condition
#phi = formula string
# alphabet = list of characters
rs = set()
alphas = set(product(alphabet, repeat= len(alphabet)))
count = 0
for alpha in alphas:
#print("map:", alpha)
phi_alpha = substitute_map_string(phi, alpha)
#print("new formula:", phi_alpha)
equivalence = "(({})->({})) & (({})->({}))".format(phi, phi_alpha, phi_alpha, phi)
print(equivalence)
parser = LTLfParser()
formula_str = equivalence
formula = parser(formula_str)
dfa = formula.to_dfa()
print(dfa)
if check_equivalence(dfa):
rs.add(alpha)
end_time = datetime.datetime.now()
time_diff = (end_time - start_time)
execution_time = time_diff.total_seconds()
return rs, execution_time
def check_equivalence(dfa_string):
return dfa_string == 'digraph MONA_DFA {\n rankdir = LR;\n center = true;\n size = "7.5,10.5";\n edge [fontname = Courier];\n node [height = .5, width = .5];\n node [shape = doublecircle]; 1;\n node [shape = circle]; 1;\n init [shape = plaintext, label = ""];\n init -> 1;\n 1 -> 1 [label="true"];\n}'
def substitute_map_string(trace, alpha):
#trace = str(trace)
#print(trace)
#print(alpha)
l= list(map(lambda item: sub_char(item, alpha), trace))
new_string = ""
for char in l:
new_string += char
return new_string
#print("new trace: ", trace)
#for i, rep in enumerate(alpha):
# trace = trace.replace(i, rep)
# print(trace)
def sub_char(item, alpha):
try:
return str(alpha[int(item)])
except:
return item