59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
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from Engine.Node import Node
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from Engine.PathFinder import PathFinder
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class GeneticFinder(PathFinder):
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def __init__(self, board, dTree):
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super().__init__(board, dTree)
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self.board = board
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self.openList = []
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self.cameFrom = {}
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self.gScore = {}
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self.fScore = {}
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def bombDistance(self,startState, endState):
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x = Node(startState, None)
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self.openList.append(x)
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self.gScore[x] = 0
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self.fScore[x] = 0
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self.endState = endState
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cameFrom = dict()
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cameFrom[x] = None
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while self.openList:
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current = self.minKey(self.fScore, self.openList)
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if self.checkGoal(current):
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return self.constructActions(current, startState)
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self.openList.remove(current)
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for next in self.getNeighbour(current):
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tentativeGScore = self.gScore.get(current) + self.weight(next)
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if tentativeGScore < self.gScore.get(next, float('inf')):
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self.cameFrom[next] = current
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next.parent = current
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self.gScore[next] = tentativeGScore
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self.fScore[next] = tentativeGScore + self.heuristic(startState, next)
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if next not in self.openList:
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self.openList.append(next)
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return []
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def checkGoal(self, current):
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if current.state.getPoint().__eq__(self.endState.getPoint()):
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bomb = self.board.getBomb(current.state.getPoint())
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bombMapping = bomb.getMapping()
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if(bombMapping[0] != None):
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actionOnBomb = self.dTree.mapAction(self.dTree.getTree().predict([bombMapping])[0])
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self.goal = Node(current, actionOnBomb)
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else:
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self.goal = Node(current, None)
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return True
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return False
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def getDistance(self,startState, endState):
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distance = 0
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for state in self.bombDistance(startState,endState):
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distance += 1
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return distance
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