weighted puddles, fixed wall destination
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7324fc47d9
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@ -11,7 +11,7 @@ from PatchAgent import PatchAgent
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from PatchType import PatchType
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from data.GameConstants import GameConstants
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from decision.ActionType import ActionType
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from pathfinding.dlaMarcina import PathFinderOnStates, PathFinderState
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from pathfinding.Pathfinder import PathFinderOnStates, PathFinderState
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from util.PathDefinitions import GridLocation, GridWithWeights
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@ -43,7 +43,7 @@ class GameModel(Model):
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self.grid.place_agent(self.forklift_agent, (x, y))
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self.forklift_agent.current_position = (x, y)
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start, goal = (x, y), (8, 8)
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start, goal = (x, y), (2, 3)
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pathFinder = PathFinderOnStates(
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self.game_constants,
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@ -13,7 +13,7 @@ class GameConstants:
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# order_pos: GridLocation,
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# special_positions: Dict[ItemType, GridLocation],
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walls: [GridLocation],
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puddles: [GridLocation]
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diffTerrain: [GridLocation]
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):
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self.grid_width = grid_width
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self.grid_height = grid_height
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@ -21,4 +21,4 @@ class GameConstants:
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# self.order_pos = order_pos
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# self.special_positions = special_positions
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self.walls = walls
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self.puddles = puddles
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self.diffTerrain = diffTerrain
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4
main.py
4
main.py
@ -58,10 +58,10 @@ if __name__ == '__main__':
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scale = base / gridWidth
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diagram4 = GridWithWeights(gridWidth, gridHeight)
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diagram4.walls = [(6, 5), (6, 6), (6, 7), (6, 8), (2, 3), (2, 4)]
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diagram4.walls = [(6, 5), (6, 6), (6, 7), (6, 8), (2, 3), (2, 4), (3, 4), (4, 4), (6, 4)]
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diagram5 = GridWithWeights(gridWidth, gridHeight)
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diagram5.puddles = [(2, 2), (2, 5)]
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diagram5.puddles = [(2, 2), (2, 5), (5, 4)]
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grid = CanvasGrid(agent_portrayal, gridWidth, gridHeight, scale * gridWidth, scale * gridHeight)
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@ -70,6 +70,9 @@ class PathFinderOnStates:
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return True
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def createState(self, currState: PathFinderState, action: ActionType) -> PathFinderState:
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if currState.agent_position in self.game_constants.diffTerrain:
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cost = currState.cost + 5
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else:
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cost = currState.cost + 1
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last_action = action
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action_taken: List[ActionType] = []
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@ -97,30 +100,29 @@ class PathFinderOnStates:
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# generowanie stanu
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# sprawdz w ktorym kierunku obrocony
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possibleNextStates: List[PathFinderState] = []
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if self.isMovePossible(currState):
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possibleNextStates.append(self.createState(currState, ActionType.MOVE))
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if currState.agent_direction == Direction.top:
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_RIGHT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_LEFT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_DOWN))
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if self.isMovePossible(currState):
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possibleNextStates.append(self.createState(currState, ActionType.MOVE))
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elif currState.agent_direction == Direction.down:
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_RIGHT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_LEFT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_UP))
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if self.isMovePossible(currState):
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possibleNextStates.append(self.createState(currState, ActionType.MOVE))
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elif currState.agent_direction == Direction.left:
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_RIGHT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_UP))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_DOWN))
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if self.isMovePossible(currState):
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possibleNextStates.append(self.createState(currState, ActionType.MOVE))
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elif currState.agent_direction == Direction.right:
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_UP))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_LEFT))
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possibleNextStates.append(self.createState(currState, ActionType.ROTATE_DOWN))
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if self.isMovePossible(currState):
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possibleNextStates.append(self.createState(currState, ActionType.MOVE))
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return possibleNextStates
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def getActionList(self) -> List[ActionType]:
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@ -130,10 +132,10 @@ class PathFinderOnStates:
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item: PrioritizedItem = self.queue.get()
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best_state: PathFinderState = item.item
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if best_state.agent_position == self.goal:
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if best_state.agent_position == self.goal or (self.heuristic(best_state.agent_position, self.goal) == 1
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and self.goal in self.game_constants.walls):
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break
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# dodajesz do kolejki stany z expansion (po cost)
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for state in self.expansion(best_state):
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s_tuple = (state.agent_position[0], state.agent_position[1], state.agent_direction)
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@ -143,26 +145,3 @@ class PathFinderOnStates:
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already_visited[s_tuple] = state
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return best_state.action_taken
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# do kosztu dokładam koszt starego stanu plus 1
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# def a_star(self,stateTree:StateTree, start: Tuple[int, int], goal: Tuple[int, int]):
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# frontier = PriorityQueue()
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# frontier.put(start, 0)
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# came_from = dict()
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# cost_so_far = dict()
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# came_from[start] = None
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# cost_so_far[start] = 0
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#
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# while not frontier.empty():
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# current = frontier.get()
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#
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# if current == goal:
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# break
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#
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# for next in graph.neighbors(current):
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# new_cost = cost_so_far[current] + graph.cost(current, next)
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# if next not in cost_so_far or new_cost < cost_so_far[next]:
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# cost_so_far[next] = new_cost
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# priority = new_cost + heuristic(goal, next)
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# frontier.put(next, priority)
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# came_from[next] = current
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@ -1,109 +0,0 @@
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from enum import Enum
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from typing import Tuple, Dict
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from data import GameConstants, Direction
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def getHotSpot(game:GameConstants) -> (int, int):
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pass
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def isOrderReady(game:GameConstants) -> bool:
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pass
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def getReadyOrderId(game:GameConstants) -> int:
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pass
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class Action():
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def __init__(self, game: GameConstants):
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self.game = GameConstants
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def rotate(self, direction: Direction) -> GameConstants:
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self.game.agentDirection = direction
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pass
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def move(self) -> GameConstants:
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# w zaleznosci od kierunku napierdala do przodu
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pass
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def special(self) -> GameConstants:
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# w zaleznosci od miejsca gdzie jest i czy ma cos na lapie odklada albo bierze przedmiot
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pass
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def orderOut(self, orderId: int) -> GameConstants:
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# nalicza punkty wypierdalaorder i czysci orderStock
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pass
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def heuristic(a: Tuple[int, int], b: Tuple[int, int]) -> float:
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(x1, y1) = a
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(x2, y2) = b
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return abs(x1 - x2) + abs(y1 - y2)
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class PossibleMoves(Enum):
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move = 1
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rotateLeft = 2
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rotateDown = 3
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rotateRight = 4
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rotateTop = 5
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def getRotationEvaluation(direction: Direction):
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# get evaluationForMoveAfterRotation
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return 1.0
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def evaluateMoves(game: GameConstants) -> Dict:
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posibleMoves = Dict
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currPos = game.agentPos
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gameCopy = game.getCopy()
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getRotationEvaluation()
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posibleMoves[PossibleMoves.move] = heuristic(currPos, Action(gameCopy).move().agentPos)
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posibleMoves[PossibleMoves.rotateTop] = getRotationEvaluation(Direction.Direction.top)
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posibleMoves[PossibleMoves.rotateLeft] = getRotationEvaluation(Direction.Direction.left)
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posibleMoves[PossibleMoves.rotateDown] = getRotationEvaluation(Direction.Direction.down)
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posibleMoves[PossibleMoves.rotateRight] = getRotationEvaluation(Direction.Direction.right)
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return posibleMoves
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def getIndex(value: float, dict: Dict) -> PossibleMoves:
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for key, val in dict:
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if val == value:
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return key
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def getMaxFromList(list: [float]) -> float:
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maxi = -10000000
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for i in range(len(list)):
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if list[i] > maxi:
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maxi = list[i]
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return maxi
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def getBestPossibleMove(game: GameConstants) -> PossibleMoves:
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movesDict = evaluateMoves()
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bestChoice = getMaxFromList(movesDict.values())
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return getIndex(bestChoice, movesDict)
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def getBestMove(game: GameConstants) -> GameConstants:
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gameCopy = game.getCopy()
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bestPossibleMove = getBestPossibleMove(gameCopy)
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if bestPossibleMove == PossibleMoves.move:
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return Action(gameCopy).move()
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elif bestPossibleMove == PossibleMoves.rotateTop:
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return Action(gameCopy).rotate(Direction.Direction.top)
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elif bestPossibleMove == PossibleMoves.rotateLeft:
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return Action(gameCopy).rotate(Direction.Direction.left)
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elif bestPossibleMove == PossibleMoves.rotateDown:
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return Action(gameCopy).rotate(Direction.Direction.down)
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else:
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return Action(gameCopy).rotate(Direction.Direction.right)
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def nastepnik(game: GameConstants) -> GameConstants:
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if isOrderReady(game) > -1:
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return Action(game.getCopy()).orderOut(getReadyOrderId(game))
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elif game.agentPos == getHotSpot(game):
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return Action(game.getCopy()).special()
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else:
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return getBestMove(game)
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