def _search(grid=grid, init=init, goal=goal):
unchecked = [[0, None] + init]
checked = []
expansion = [[-1 for col in range(len(grid[0]))]
for row in range(len(grid))]
expansion_index = 0
actions = [[-1 for col in range(len(grid[0]))] for row in range(len(grid))]
while unchecked:
# sort by g-value
unchecked.sort(key=lambda x: x[0], reverse=True)
# expand
g, action, y, x = unchecked.pop()
checked.append([y, x])
actions[y][x] = action
expansion[y][x] = expansion_index
expansion_index += 1
if [y, x] == goal:
return [g, y, x], actions
for action, dt in enumerate(delta):
pos = move(grid, [y, x], dt)
if pos and pos not in checked:
node = [g + 1, action] + pos
# use a set for this?
if node not in unchecked:
unchecked.append(node)
return FAIL, actions
def _search(grid=grid, init=init, goal=goal):
open_nodes = [[0] + init]
checked_nodes = []
expansion = [[-1 for col in range(len(grid[0]))]
for row in range(len(grid))]
expansion_index = 0
while open_nodes:
# sort by g-value
open_nodes.sort(key=lambda x: x[0], reverse=True)
# expand
g, y, x = open_nodes.pop()
checked_nodes.append([y, x])
expansion[y][x] = expansion_index
expansion_index += 1
if [y, x] == goal:
return [g, y, x], expansion
for d in delta:
t = move(grid, [y, x], d)
if t and t not in checked_nodes:
new_node = [g + 1] + t
# use a set for here?
if new_node not in open_nodes:
open_nodes.append(new_node)
return 'fail', expansion
def _optimum_policy(grid=grid, goal=goal):
value = [[99 for col in range(len(grid[0]))]
for row in range(len(grid))]
policy = [[' ' for col in range(len(grid[0]))]
for row in range(len(grid))]
y, x = goal
value[y][x] = 0
policy[y][x] = '*'
updated = True
while updated:
updated = False
for y in xrange(len(grid)):
for x in xrange(len(grid[0])):
if [y, x] != goal and grid[y][x] == 0:
for index, action in enumerate(delta):
pos = move(grid, [y, x], action)
if pos:
v = value[pos[0]][pos[1]] + cost_step
if v < value[y][x]:
value[y][x] = v
policy[y][x] = delta_name[index]
updated = True
return value, policy
def _optimum_policy(grid=grid, goal=goal):
value = [[99 for col in range(len(grid[0]))] for row in range(len(grid))]
policy = [[' ' for col in range(len(grid[0]))] for row in range(len(grid))]
y, x = goal
value[y][x] = 0
policy[y][x] = '*'
updated = True
while updated:
updated = False
for y in xrange(len(grid)):
for x in xrange(len(grid[0])):
if [y, x] != goal and grid[y][x] == 0:
for index, action in enumerate(delta):
pos = move(grid, [y, x], action)
if pos:
v = value[pos[0]][pos[1]] + cost_step
if v < value[y][x]:
value[y][x] = v
policy[y][x] = delta_name[index]
updated = True
return value, policy
def _search(grid=grid, init=init, goal=goal):
open_nodes = [[0] + init]
checked_nodes = []
expansion = [[-1 for col in range(len(grid[0]))]
for row in range(len(grid))]
expansion_index = 0
while open_nodes:
# sort by g-value
open_nodes.sort(key=lambda x: x[0], reverse=True)
# expand
g, y, x = open_nodes.pop()
checked_nodes.append([y, x])
expansion[y][x] = expansion_index
expansion_index += 1
if [y, x] == goal:
return [g, y, x], expansion
for d in delta:
t = move(grid, [y, x], d)
if t and t not in checked_nodes:
new_node = [g + 1] + t
# use a set for here?
if new_node not in open_nodes:
open_nodes.append(new_node)
return 'fail', expansion
def _search(grid=grid, init=init, goal=goal):
unchecked = [[0, None] + init]
checked = []
expansion = [[-1 for col in range(len(grid[0]))] for row in range(len(grid))]
expansion_index = 0
actions = [[-1 for col in range(len(grid[0]))] for row in range(len(grid))]
while unchecked:
# sort by g-value
unchecked.sort(key=lambda x: x[0], reverse=True)
# expand
g, action, y, x = unchecked.pop()
checked.append([y, x])
actions[y][x] = action
expansion[y][x] = expansion_index
expansion_index += 1
if [y, x] == goal:
return [g, y, x], actions
for action, dt in enumerate(delta):
pos = move(grid, [y, x], dt)
if pos and pos not in checked:
node = [g + 1, action] + pos
# use a set for this?
if node not in unchecked:
unchecked.append(node)
return FAIL, actions
def _search(grid=grid, init=init, goal=goal):
y, x = init
g = 0
h = heuristic[y][x]
f = g + h
# action = None
# unchecked = [[f, g, h, action, y, x]]
unchecked = [[f, g, y, x]]
checked = [[0 for col in range(len(grid[0]))]
for row in range(len(grid))]
expansion = [[-1 for col in range(len(grid[0]))]
for row in range(len(grid))]
expansion_index = 0
# actions = [[-1 for col in range(len(grid[0]))]
# for row in range(len(grid))]
while unchecked:
# sort by g-value
unchecked.sort(reverse=True)
# expand
# f, g, h, action, y, x = unchecked.pop()
# print f, g, h, action, y, x
f, g, y, x = unchecked.pop()
checked[y][x] = 1
# actions[y][x] = action
expansion[y][x] = expansion_index
expansion_index += 1
if [y, x] == goal:
return [g, y, x], expansion
for action, dt in enumerate(delta):
pos = move(grid, [y, x], dt)
if pos:
y1, x1 = pos
if not checked[y1][x1]:
g1 = g + cost
h = heuristic[y1][x1]
# node = [f, g1, h, action] + pos
node = [g1 + h, g1, y1, x1]
# use a set for this?
if node not in unchecked:
unchecked.append(node)
return FAIL, expansion
def _compute_value(grid=grid, goal=goal):
value = [[99 for col in range(len(grid[0]))] for row in range(len(grid))]
value[goal[0]][goal[1]] = 0
updated = True
while updated:
updated = False
for y in xrange(len(grid)):
for x in xrange(len(grid[0])):
if [y, x] != goal and grid[y][x] == 0:
for action in delta:
pos = move(grid, [y, x], action)
if pos:
v = value[pos[0]][pos[1]] + cost_step
if v < value[y][x]:
value[y][x] = v
updated = True
return value
def _compute_value(grid=grid, goal=goal):
value = [[99 for col in range(len(grid[0]))] for row in range(len(grid))]
value[goal[0]][goal[1]] = 0
updated = True
while updated:
updated = False
for y in xrange(len(grid)):
for x in xrange(len(grid[0])):
if [y, x] != goal and grid[y][x] == 0:
for action in delta:
pos = move(grid, [y, x], action)
if pos:
v = value[pos[0]][pos[1]] + cost_step
if v < value[y][x]:
value[y][x] = v
updated = True
return value
