image_recognition #5
@ -1,8 +1,9 @@
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class Node:
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class Node:
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def __init__(self, state, parent='', action=''):
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def __init__(self, state, parent='', action='', distance=0):
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self.state = state
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self.state = state
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self.parent = parent
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self.parent = parent
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self.action = action
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self.action = action
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self.distance = distance
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class Search:
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class Search:
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def __init__(self, cell_size, cell_number):
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def __init__(self, cell_size, cell_number):
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@ -30,11 +31,27 @@ class Search:
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possible = [['left', x, y, 'DOWN'], ['right', x, y, 'UP']]
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possible = [['left', x, y, 'DOWN'], ['right', x, y, 'UP']]
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if x != 0: possible.append(['move', x - self.cell_size, y, 'LEFT'])
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if x != 0: possible.append(['move', x - self.cell_size, y, 'LEFT'])
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return possible
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return possible
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def cost(self, node, stones, goal, flowers):
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# cost = node.distance
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cost = 0
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# cost += 10 if stones[node.state[0], node.state[1]] == 1 else 1
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cost += 1000000 if (node.state[0], node.state[1]) in stones else 1
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cost += 30 if (node.state[0], node.state[1]) in flowers else 1
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if node.parent:
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node = node.parent
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cost += node.distance # should return only elem.action in prod
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return cost
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def heuristic(self, node, goal):
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return abs(node.state[0] - goal[0]) + abs(node.state[1] - goal[1])
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#bandaid to know about stones
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#bandaid to know about stones
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def astarsearch(self, istate, goaltest, stones):
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def astarsearch(self, istate, goaltest, stones, flowers):
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#to be expanded
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#to be expanded
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def cost(x, y):
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def cost_old(x, y):
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if (x, y) in stones:
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if (x, y) in stones:
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return 10
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return 10
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else:
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else:
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@ -45,7 +62,12 @@ class Search:
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y = istate[1]
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y = istate[1]
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angle = istate[2]
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angle = istate[2]
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fringe = [(Node([x, y, angle]), cost(x, y))] # queue (moves/states to check)
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# fringe = [(Node([x, y, angle]), cost_old(x, y))] # queue (moves/states to check)
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fringe = [(Node([x, y, angle]))] # queue (moves/states to check)
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fringe[0].distance = self.cost(fringe[0], stones, goaltest, flowers)
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fringe.append((Node([x, y, angle]), self.cost(fringe[0], stones, goaltest, flowers)))
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fringe.pop(0)
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explored = []
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explored = []
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while True:
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while True:
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@ -72,8 +94,11 @@ class Search:
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for (action, state_x, state_y, state_angle) in self.succ(elem.state):
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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)
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x = Node([state_x, state_y, state_angle], elem, action)
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x.parent = elem
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priority = cost(state_x, state_y)
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priority = self.cost(elem, stones, goaltest, flowers) + self.heuristic(elem, goaltest)
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elem.distance = priority
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# priority = cost_old(x, y) + self.heuristic(elem, goaltest)
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fringe_states = [node.state for (node, p) in fringe]
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fringe_states = [node.state for (node, p) in fringe]
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if x.state not in fringe_states and x.state not in explored:
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if x.state not in fringe_states and x.state not in explored:
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2
main.py
2
main.py
@ -102,7 +102,7 @@ class Game:
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angles = {0: 'UP', 90: 'RIGHT', 270: 'LEFT', 180: 'DOWN'}
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angles = {0: 'UP', 90: 'RIGHT', 270: 'LEFT', 180: 'DOWN'}
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#bandaid to know about stones
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#bandaid to know about stones
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tractor_next_moves = astar_search_object.astarsearch(
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tractor_next_moves = astar_search_object.astarsearch(
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[self.tractor.x, self.tractor.y, angles[self.tractor.angle]], [random_x, random_y], self.blocks.stones)
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[self.tractor.x, self.tractor.y, angles[self.tractor.angle]], [random_x, random_y], self.blocks.stones, self.flower_body)
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else:
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else:
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self.tractor.move(tractor_next_moves.pop(0)[0], self.cell_size, self.cell_number)
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self.tractor.move(tractor_next_moves.pop(0)[0], self.cell_size, self.cell_number)
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elif event.type == QUIT:
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elif event.type == QUIT:
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Reference in New Issue
Block a user