si23traktor/astar_search.py

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class Node:
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def __init__(self, state, parent='', action='', distance=0):
self.state = state
self.parent = parent
self.action = action
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self.distance = distance
class Search:
def __init__(self, cell_size, cell_number):
self.cell_size = cell_size
self.cell_number = cell_number
def succ(self, state):
x = state[0]
y = state[1]
angle = state[2]
match(angle):
case 'UP':
possible = [['left', x, y, 'LEFT'], ['right', x, y, 'RIGHT']]
if y != 0: possible.append(['move', x, y - self.cell_size, 'UP'])
return possible
case 'RIGHT':
possible = [['left', x, y, 'UP'], ['right', x, y, 'DOWN']]
if x != self.cell_size*(self.cell_number-1): possible.append(['move', x + self.cell_size, y, 'RIGHT'])
return possible
case 'DOWN':
possible = [['left', x, y, 'RIGHT'], ['right', x, y, 'LEFT']]
if y != self.cell_size*(self.cell_number-1): possible.append(['move', x, y + self.cell_size, 'DOWN'])
return possible
case 'LEFT':
possible = [['left', x, y, 'DOWN'], ['right', x, y, 'UP']]
if x != 0: possible.append(['move', x - self.cell_size, y, 'LEFT'])
return possible
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def cost(self, node, stones, goal, flowers):
# cost = node.distance
cost = 0
# cost += 10 if stones[node.state[0], node.state[1]] == 1 else 1
cost += 1000 if (node.state[0], node.state[1]) in stones else 1
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cost += 300 if ((node.state[0]), (node.state[1])) in flowers else 1
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if node.parent:
node = node.parent
cost += node.distance # should return only elem.action in prod
return cost
def heuristic(self, node, goal):
return abs(node.state[0] - goal[0]) + abs(node.state[1] - goal[1])
#bandaid to know about stones
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def astarsearch(self, istate, goaltest, cStones, cFlowers):
#to be expanded
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def cost_old(x, y):
if (x, y) in stones:
return 10
else:
return 1
x = istate[0]
y = istate[1]
angle = istate[2]
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stones = [(x*50, y*50) for (x, y) in cStones]
flowers = [(x*50, y*50) for (x, y) in cFlowers]
print(stones)
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# fringe = [(Node([x, y, angle]), cost_old(x, y))] # queue (moves/states to check)
fringe = [(Node([x, y, angle]))] # queue (moves/states to check)
fringe[0].distance = self.cost(fringe[0], stones, goaltest, flowers)
fringe.append((Node([x, y, angle]), self.cost(fringe[0], stones, goaltest, flowers)))
fringe.pop(0)
explored = []
while True:
if len(fringe) == 0:
return False
fringe.sort(key=lambda x: x[1])
elem = fringe.pop(0)[0]
# if goal_test(elem.state):
# return
# print(elem.state[0], elem.state[1], elem.state[2])
if elem.state[0] == goaltest[0] and elem.state[1] == goaltest[1]: # checks if we reached the given point
steps = []
while elem.parent:
steps.append([elem.action, elem.state[0], elem.state[1]]) # should return only elem.action in prod
elem = elem.parent
steps.reverse()
print(steps) # only for dev
return steps
explored.append(elem.state)
for (action, state_x, state_y, state_angle) in self.succ(elem.state):
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x = Node([state_x, state_y, state_angle], elem, action)
x.parent = elem
priority = self.cost(elem, stones, goaltest, flowers) + self.heuristic(elem, goaltest)
elem.distance = priority
# priority = cost_old(x, y) + self.heuristic(elem, goaltest)
fringe_states = [node.state for (node, p) in fringe]
if x.state not in fringe_states and x.state not in explored:
fringe.append((x, priority))
elif x.state in fringe_states:
for i in range(len(fringe)):
if fringe[i][0].state == x.state:
if fringe[i][1] > priority:
fringe[i] = (x, priority)