def more_pour_problem(capacities, goal, start=None):
# your code here
if not start:
start = (0,) * len(capacities)
return shortest_path_search(start, more_successors(capacities), lambda state: goal in state)
'''
Created on Sep 15, 2013
@author: pglauner
'''
from algorithms.routing.shortest_path import shortest_path_search
from algorithms.routing.lowest_cost import lowest_cost_search
from algorithms.routing.a_star.simple import a_star as a_star_simple
from algorithms.routing.a_star.queue_based import a_star as a_star_queue
from algorithms.routing.test_graphs.test_graphs import tricky_graph
from algorithms.routing.test_graphs.phrase_graphs import simple_phrase
from algorithms.routing.test_graphs.graph_utils import action_cost, is_goal, successors
if __name__ == '__main__':
print shortest_path_search(0, successors(tricky_graph), is_goal(100))
print lowest_cost_search(0, successors(tricky_graph), is_goal(100), action_cost)
print a_star_simple(tricky_graph, 0, 100)
print a_star_queue(tricky_graph, 0, 100)
print
print shortest_path_search(0, successors(simple_phrase), is_goal(1))
print lowest_cost_search(0, successors(simple_phrase), is_goal(1), action_cost)
print a_star_simple(simple_phrase, 0, 1)
print a_star_queue(simple_phrase, 0, 1)
'''
Created on Sep 15, 2013
@author: pglauner
'''
from algorithms.routing.shortest_path import shortest_path_search
from algorithms.routing.lowest_cost import lowest_cost_search
from algorithms.routing.a_star.simple import a_star as a_star_simple
from algorithms.routing.a_star.queue_based import a_star as a_star_queue
from algorithms.routing.test_graphs.test_graphs import tricky_graph
from algorithms.routing.test_graphs.phrase_graphs import simple_phrase
from algorithms.routing.test_graphs.graph_utils import action_cost, is_goal, successors
if __name__ == '__main__':
print shortest_path_search(0, successors(tricky_graph), is_goal(100))
print lowest_cost_search(0, successors(tricky_graph), is_goal(100),
action_cost)
print a_star_simple(tricky_graph, 0, 100)
print a_star_queue(tricky_graph, 0, 100)
print
print shortest_path_search(0, successors(simple_phrase), is_goal(1))
print lowest_cost_search(0, successors(simple_phrase), is_goal(1),
action_cost)
print a_star_simple(simple_phrase, 0, 1)
print a_star_queue(simple_phrase, 0, 1)
for z in (x, y):
if z == "M":
m1 -= 1
m2 += 1
action += "M"
if z == "C":
c1 -= 1
c2 += 1
action += "C"
if all(x >= 0 for x in (m1, c1, b1, m2, c2, b2)):
if B1:
res[(m1, c1, b1, m2, c2, b2)] = action + "->"
elif B2:
res[(m2, c2, b1, m1, c1, b2)] = "<-" + action
return res
def is_goal(start):
def g(state):
return state == (0, 0, 0) + start
return g
if __name__ == "__main__":
start = m1, c1, b1, m2, c2, b2 = 3, 3, 1, 0, 0, 0
print shortest_path_search(start, successors, is_goal(start[0:3]))
print lowest_cost_search(start, successors, is_goal(start[0:3]), lambda action: 1)
if z == 'M':
m1 -= 1
m2 += 1
action += 'M'
if z == 'C':
c1 -= 1
c2 += 1
action += 'C'
if all(x >= 0 for x in (m1, c1, b1, m2, c2, b2)):
if B1:
res[(m1, c1, b1, m2, c2, b2)] = action + '->'
elif B2:
res[(m2, c2, b1, m1, c1, b2)] = '<-' + action
return res
def is_goal(start):
def g(state):
return state == (0, 0, 0) + start
return g
if __name__ == '__main__':
start = m1, c1, b1, m2, c2, b2 = 3, 3, 1, 0, 0, 0
print shortest_path_search(start, successors, is_goal(start[0:3]))
print lowest_cost_search(start, successors, is_goal(start[0:3]),
lambda action: 1)
res = {}
empty_y, empty_x = get_y_x(state.index('E'), N)
row_idx1 = empty_y * N
row_idx2 = row_idx1 + N
move_row_or_col(state, res, row_idx1, row_idx2, 'Row')
col_idx1 = empty_x
col_idx2 = N * (N - 1) + empty_x % N + 1
move_row_or_col(state, res, col_idx1, col_idx2, 'Col', N)
return res
return successors_n
def is_goal(N):
def is_goal_n(state):
return tuple(range(N*N-1) + ['E']) == state
return is_goal_n
if __name__ == '__main__':
for start in tile_games:
N = tile_lens[len(start)]
print start
shortest_path = shortest_path_search(start, successors(N), is_goal(N))
print shortest_path
print len(shortest_path) / 2, 'moves'
Created on Sep 8, 2013
@author: pglauner
'''
from algorithms.routing.shortest_path import shortest_path_search
from algorithms.routing.lowest_cost import lowest_cost_search
def successors(X, Y):
def sc(state):
x, y = state
assert x <= X and y <= Y
return {((0, y+x) if y+x <= Y else (x-(Y-y), (Y))): 'x->y',
((x+y, 0) if x+y <= X else (X, (y-(X-x)))): 'x<-y',
(X, y): 'fill x',
(x, Y): 'fill y',
(0, y): 'empty x',
(x, 0): 'empty y'}
return sc
if __name__ == '__main__':
res = shortest_path_search((0, 0), successors(418, 986), lambda state: state == (6, 0))
print res
print '%s transitions' % (len(res) / 2)
print
res = lowest_cost_search((0, 0), successors(418, 986), lambda state: state == (6, 0), lambda action: 1)
print res
print '%s transitions' % (len(res) / 2)
