def occurs_in(s1, lst):
index = 0
for s2 in lst:
if Problem.DEEP_EQUALS(s1, s2[0]):
return index
else:
index = index + 1
return -1
def IterativeAStar(initial_state):
global COUNT, BACKLINKS
OPEN = [initial_state]
CLOSED = []
BACKLINKS[Problem.HASHCODE(initial_state)] = -1
g = {Problem.HASHCODE(initial_state): 0}
while OPEN != []:
S = OPEN[0]
del OPEN[0]
CLOSED.append(S)
if Problem.GOAL_TEST(S):
print(Problem.GOAL_MESSAGE_FUNCTION(S))
backtrace(S)
return
COUNT += 1
if (COUNT % 32) == 0:
print(".", end="")
if (COUNT % 128) == 0:
print("COUNT = " + str(COUNT))
print("len(OPEN)=" + str(len(OPEN)))
print("len(CLOSED)=" + str(len(CLOSED)))
L = []
for op in Problem.OPERATORS:
#Optionally uncomment the following when debugging
#a new problem formulation.
#print("Trying operator: "+op.name)
if op.precond(S):
new_state = op.state_transf(S)
if not occurs_in(new_state, CLOSED):
L.append(new_state)
BACKLINKS[Problem.HASHCODE(new_state)] = S
g[Problem.HASHCODE(new_state)] = g[Problem.HASHCODE(S)] + 1
#Uncomment for debugging:
#print(Problem.DESCRIBE_STATE(new_state))
for s2 in L:
for i in range(len(OPEN)):
if Problem.DEEP_EQUALS(s2, OPEN[i]):
del OPEN[i]
break
OPEN = L + OPEN
OPEN = sorted(OPEN,
key=lambda s: g[Problem.HASHCODE(s)] + heuristics(s))
def IterateAStar(initial_state):
global COUNT, BACKLINKS
OPEN = [[initial_state, heuristics(initial_state)]]
CLOSED = []
# print(initial_state)
COST = {Problem.HASHCODE(initial_state): 0}
BACKLINKS[Problem.HASHCODE(initial_state)] = -1
while OPEN != []:
S = OPEN[0]
del OPEN[0]
CLOSED.append(S)
if Problem.GOAL_TEST(S[0]):
print(Problem.GOAL_MESSAGE_FUNCTION(S[0]))
backtrace(S[0])
return
COUNT += 1
if (COUNT % 32)==0:
print(".",end="")
if (COUNT % 128)==0:
print("COUNT = "+str(COUNT))
print("len(OPEN)="+str(len(OPEN)))
print("len(CLOSED)="+str(len(CLOSED)))
L = []
# for each possible child in S (state)
for op in Problem.OPERATORS:
# is a child
if op.precond(S[0]):
new_state = op.state_transf(S[0])
# index of occurrence in CLOSED
occur_closed = occurs_in(new_state, CLOSED)
# index of occurence in OPEN
occur_open = occurs_in(new_state, OPEN)
# the moves made so far + 1
new_cost = COST[Problem.HASHCODE(S[0])] + 1
# place in neighbor if new state
if occur_closed == -1 and occur_open == -1:
L.append([new_state, heuristics(new_state)])
BACKLINKS[Problem.HASHCODE(new_state)] = S[0]
COST[Problem.HASHCODE(new_state)] = new_cost
elif occur_open > -1:
# check to see if this move is more efficient
if COST[Problem.HASHCODE(new_state)] > new_cost:
COST[Problem.HASHCODE(new_state)] = new_cost
OPEN[occur_open] = [new_state, new_cost]
# for all neighbors found, if it equals to states in OPEN,
# delete it, shouldn't occur but juuuuust in case...
for s2 in L:
for i in range(len(OPEN)):
if Problem.DEEP_EQUALS(s2, OPEN[i][0]):
del OPEN[i]; break
OPEN = L + OPEN
OPEN.sort(key=lambda x: x[1])
def occurs_in(s1, lst):
for s2 in lst:
if Problem.DEEP_EQUALS(s1, s2): return True
return False
