# END_YOUR_CODE
def is_end(self, state):
# BEGIN_YOUR_CODE
return state == ''
# END_YOUR_CODE
def succ_and_cost(self, state):
results = []
# BEGIN_YOUR_CODE
for i in range(len(state)):
action = state[:i + 1]
next_state = state[i + 1:]
cost = self.unigramCost(action)
results.append((action, next_state, cost))
return results
# END_YOUR_CODE
unigramCost, bigramCost = wordsegUtil.makeLanguageModels('leo-will.txt')
problem = SegmentationProblem('thisisnotmybeautifulhouse', unigramCost)
import backtracking_search
bts = backtracking_search.BacktrackingSearch(verbose=0)
#print bts.solve(problem)
import uniform_cost_search
ucs = uniform_cost_search.UniformCostSearch(verbose=3)
print ucs.solve(problem)
'e': 13,
'f': 45,
'g': 21,
'h': 14,
'i': -92,
'j': 33
}
def startState(self):
return 'root'
def isGoal(self, state):
if self._transitions[state] == ():
return True
def succAndCost(self, state):
actions = ['left', 'right']
next_states = self._transitions[state]
if next_states == ():
return []
costs = [self._costs[next_states[0]], self._costs[next_states[1]]]
return zip(actions, next_states, costs)
if __name__ == '__main__':
problem = PyramidProblem()
algo = backtracking_search.BacktrackingSearch()
algo.solve(problem)
print(algo.cost)
print(algo.actions)
