def randomized_maxvalue(problem, limit=100, callback=None):
seed(42)
current = LSNode(problem, problem.initial, 0)
best = current
for _ in range(limit):
if callback is not None:
callback(current)
successors = list(current.expand())
list_of_best = []
i = 0
while (i < 5):
ind = successors.index(max(successors, key=lambda node: node.state))
list_of_best.append(successors[ind])
successors.pop(ind)
i += 1
current = choice(list_of_best)
if current.state > best.state:
best = current
return best
def maxvalue(problem, limit=100, callback=None):
"""Perform a random walk in the search space and return the best solution
found. The returned value is a Node.
If callback is not None, it must be a one-argument function that will be
called at each step with the current node.
"""
current = LSNode(problem, problem.initial, 0)
best_of_best = current
#best.v = current.state.value
for _ in range(limit):
#best.v = -float('inf')
if callback is not None:
callback(current)
successors = list(current.expand())
ind = successors.index(max(successors, key=lambda node: node.state))
current = successors[ind]
if current.state > best_of_best.state:
best_of_best = current
#return current
return best_of_best
def randomized_maxvalue(problem, limit=100, callback=None):
seed(42)
current = LSNode(problem, problem.initial, 0)
best = current
for _ in range(limit):
if callback is not None:
callback(current)
successors = list(current.expand())
list_of_best = []
i = 0
while (i < 5):
ind = successors.index(max(successors,
key=lambda node: node.state))
list_of_best.append(successors[ind])
successors.pop(ind)
i += 1
current = choice(list_of_best)
if current.state > best.state:
best = current
return best
def maxvalue(problem, limit=100, callback=None):
"""Perform a random walk in the search space and return the best solution
found. The returned value is a Node.
If callback is not None, it must be a one-argument function that will be
called at each step with the current node.
"""
current = LSNode(problem, problem.initial, 0)
best_of_best = current
#best.v = current.state.value
for _ in range(limit):
#best.v = -float('inf')
if callback is not None:
callback(current)
successors = list(current.expand())
ind = successors.index(max(successors, key=lambda node: node.state))
current = successors[ind]
if current.state > best_of_best.state:
best_of_best = current
#return current
return best_of_best
