148 lines
6.5 KiB
Python
148 lines
6.5 KiB
Python
from dataclasses import dataclass, field
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from typing import List, Any
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from typing import Tuple
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from data.Direction import Direction
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from data.GameConstants import GameConstants
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from decision.ActionType import ActionType
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from util.PathDefinitions import GridLocation
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from util.PriorityQueue import PriorityQueue
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@dataclass(order=True)
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class PrioritizedItem:
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priority: float
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item: Any = field(compare=False)
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class PathFinderState:
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def __init__(self, agent_position: GridLocation, agent_direction: Direction, cost: float,
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last_action: ActionType, action_taken: List[ActionType]):
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super().__init__()
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self.agent_position = agent_position
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self.agent_direction = agent_direction
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self.cost = cost
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self.last_action = last_action
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self.action_taken = action_taken
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class PathFinderOnStates:
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def __init__(self, game_constants: GameConstants, goal: GridLocation, root_state: PathFinderState):
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super().__init__()
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self.game_constants = game_constants
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self.goal = goal
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self.queue = PriorityQueue()
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self.queue.put(PrioritizedItem(root_state.cost, root_state), root_state.cost)
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def heuristic(self, a: Tuple[int, int], b: Tuple[int, int]) -> float:
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# tutaj mozna uzyc heury np. manhatan distance (zmodyfikowany bo masz obroty a to zmienia oplacalnosc)
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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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def evaluate(self, currState: PathFinderState) -> float:
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# koszt dojscia do danego stanu+ heura
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return currState.cost + self.heuristic(currState.agent_position, self.goal)
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def getPositionAfterMove(self, currState: PathFinderState) -> GridLocation:
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if currState.agent_direction == Direction.top:
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return currState.agent_position[0], currState.agent_position[1] + 1
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elif currState.agent_direction == Direction.down:
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return currState.agent_position[0], currState.agent_position[1] - 1
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elif currState.agent_direction == Direction.right:
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return currState.agent_position[0] + 1, currState.agent_position[1]
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elif currState.agent_direction == Direction.left:
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return currState.agent_position[0] - 1, currState.agent_position[1]
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def isMovePossible(self, currState: PathFinderState) -> bool:
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positionAfterMove = self.getPositionAfterMove(currState)
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if positionAfterMove in self.game_constants.walls:
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return False
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elif positionAfterMove[0] < 0 or positionAfterMove[0] > self.game_constants.grid_width:
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return False
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elif positionAfterMove[1] < 0 or positionAfterMove[1] > self.game_constants.grid_height:
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return False
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else:
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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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action_taken.extend(currState.action_taken)
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action_taken.append(last_action)
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agent_position = currState.agent_position
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agent_direction = currState.agent_direction
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if action == ActionType.ROTATE_UP:
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agent_direction = Direction.top
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elif action == ActionType.ROTATE_DOWN:
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agent_direction = Direction.down
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elif action == ActionType.ROTATE_LEFT:
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agent_direction = Direction.left
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elif action == ActionType.ROTATE_RIGHT:
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agent_direction = Direction.right
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elif action == ActionType.MOVE:
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agent_position = self.getPositionAfterMove(currState)
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return PathFinderState(agent_position, agent_direction, cost, last_action, action_taken)
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def expansion(self, currState: PathFinderState) -> List[PathFinderState]:
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# dla stanu sprawdzamy jakie akcje z tego miejsca mozemy podjac (ActionType)
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# reprezentacja kazdego stanu co moge podjac z tego miejsca
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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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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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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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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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return possibleNextStates
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def getActionList(self) -> List[ActionType]:
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already_visited = {}
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while not self.queue.empty():
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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 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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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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if s_tuple not in already_visited:
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priority = self.evaluate(state)
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self.queue.put(PrioritizedItem(priority, state), priority)
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already_visited[s_tuple] = state
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return best_state.action_taken
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