astar for MIkołaj Gawor
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dd34b7341a
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311a2d0757
62
bfs.py
62
bfs.py
@ -4,30 +4,44 @@ from city import City
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from gridCellType import GridCellType
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from gridCellType import GridCellType
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from agentActionType import AgentActionType
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from agentActionType import AgentActionType
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from agentOrientation import AgentOrientation
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from agentOrientation import AgentOrientation
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from queue import Queue
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from queue import Queue, PriorityQueue
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from turnCar import turn_left_orientation, turn_right_orientation
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from turnCar import turn_left_orientation, turn_right_orientation
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class Succ:
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class Succ:
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state: AgentState
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state: AgentState
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action: AgentActionType
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action: AgentActionType
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##cost: int
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cost: int
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predicted_cost: int
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def __init__(self, state: AgentState, action: AgentActionType) -> None:
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def __init__(self, state: AgentState, action: AgentActionType, cost: int, predicted_cost: int) -> None:
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self.state = state
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self.state = state
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self.action = action
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self.action = action
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##self.cost = cost
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self.cost = cost
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self.predicted_cost = cost
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def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> list[AgentActionType]:
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class SuccList:
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q: Queue[list[Succ]] = Queue()
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succ_list: list[Succ]
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def __init__(self, succ_list: list[Succ]) -> None:
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self.succ_list = succ_list
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def __lt__(self, other):
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return self.succ_list[-1].predicted_cost < other.succ_list[-1].predicted_cost
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def __gt__(self, other):
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return self.succ_list[-1].predicted_cost > other.succ_list[-1].predicted_cost
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def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[AgentActionType]:
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q: PriorityQueue[SuccList] = PriorityQueue()
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visited: list[AgentState] = []
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visited: list[AgentState] = []
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startStates: list[Succ] = [Succ(startState, AgentActionType.UNKNOWN)]
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startStates: SuccList = SuccList([Succ(startState, AgentActionType.UNKNOWN, 0, _heuristics(startState.position, city))])
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q.put(startStates)
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q.put(startStates)
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while not q.empty():
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while not q.empty():
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currently_checked = q.get()
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currently_checked = q.get()
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visited.append(currently_checked[-1].state)
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visited.append(currently_checked.succ_list[-1].state)
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if is_state_success(currently_checked[-1].state, grid):
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if is_state_success(currently_checked.succ_list[-1].state, grid):
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return extract_actions(currently_checked)
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return extract_actions(currently_checked)
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successors = succ(currently_checked[-1].state)
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successors = succ(currently_checked.succ_list[-1], grid, city)
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for s in successors:
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for s in successors:
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already_visited = False
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already_visited = False
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for v in visited:
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for v in visited:
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@ -37,34 +51,38 @@ def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int],
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if already_visited:
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if already_visited:
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continue
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continue
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if is_state_valid(s.state, grid):
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if is_state_valid(s.state, grid):
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new_list = currently_checked.copy()
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new_list = currently_checked.succ_list.copy()
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new_list.append(s)
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new_list.append(s)
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q.put(new_list)
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q.put(SuccList(new_list))
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return []
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return []
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def extract_actions(successors: list[Succ]) -> list[AgentActionType]:
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def extract_actions(successors: SuccList) -> list[AgentActionType]:
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output: list[AgentActionType] = []
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output: list[AgentActionType] = []
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for s in successors:
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for s in successors.succ_list:
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if s.action != AgentActionType.UNKNOWN:
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if s.action != AgentActionType.UNKNOWN:
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output.append(s.action)
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output.append(s.action)
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return output
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return output
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def succ(state: AgentState) -> list[Succ]:
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def succ(succ: Succ, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[Succ]:
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result: list[Succ] = []
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result: list[Succ] = []
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result.append(Succ(AgentState(state.position, turn_left_orientation(state.orientation)), AgentActionType.TURN_LEFT))
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turn_left_cost = 1 + succ.cost
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result.append(Succ(AgentState(state.position, turn_right_orientation(state.orientation)), AgentActionType.TURN_RIGHT))
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result.append(Succ(AgentState(succ.state.position, turn_left_orientation(succ.state.orientation)), AgentActionType.TURN_LEFT, turn_left_cost, turn_left_cost + _heuristics(succ.state.position, city)))
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state_succ = move_forward_succ(state)
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turn_right_cost = 1 + succ.cost
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result.append(Succ(AgentState(succ.state.position, turn_right_orientation(succ.state.orientation)), AgentActionType.TURN_RIGHT, turn_right_cost, turn_right_cost + _heuristics(succ.state.position, city)))
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state_succ = move_forward_succ(succ, city, grid)
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if state_succ != None:
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if state_succ != None:
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result.append(move_forward_succ(state))
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result.append(state_succ)
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return result
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return result
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def move_forward_succ(state: AgentState) -> Succ:
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def move_forward_succ(succ: Succ, city: City, grid: Dict[Tuple[int, int], GridCellType]) -> Succ:
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position = get_next_cell(state)
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position = get_next_cell(succ.state)
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if position == None:
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if position == None:
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return None
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return None
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return Succ(AgentState(position, state.orientation), AgentActionType.MOVE_FORWARD)
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cost = get_cost_for_action(AgentActionType.MOVE_FORWARD, grid[position]) + succ.cost
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return Succ(AgentState(position, succ.state.orientation), AgentActionType.MOVE_FORWARD, cost, cost + _heuristics(position, city))
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def get_next_cell(state: AgentState) -> Tuple[int, int]:
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def get_next_cell(state: AgentState) -> Tuple[int, int]:
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6
city.py
6
city.py
@ -11,12 +11,12 @@ class City:
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cans_dict: Dict[Tuple[int, int], GarbageCan] = {}
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cans_dict: Dict[Tuple[int, int], GarbageCan] = {}
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def __init__(self) -> None:
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def __init__(self) -> None:
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self.nodes = []
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self.cans = []
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self.streets = []
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self.streets = []
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self.bumps = []
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self.bumps = []
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def add_can(self, can: GarbageCan) -> None:
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def add_can(self, can: GarbageCan) -> None:
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self.nodes.append(can)
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self.cans.append(can)
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self.cans_dict[can.position] = can
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self.cans_dict[can.position] = can
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def add_street(self, street: Street) -> None:
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def add_street(self, street: Street) -> None:
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@ -35,7 +35,7 @@ class City:
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street.render(game_context)
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street.render(game_context)
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def _render_nodes(self, game_context: GameContext) -> None:
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def _render_nodes(self, game_context: GameContext) -> None:
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for node in self.nodes:
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for node in self.cans:
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node.render(game_context)
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node.render(game_context)
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def _render_bumps(self, game_context: GameContext) -> None:
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def _render_bumps(self, game_context: GameContext) -> None:
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@ -13,7 +13,7 @@ from agentState import AgentState
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def collect_garbage(game_context: GameContext) -> None:
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def collect_garbage(game_context: GameContext) -> None:
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while True:
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while True:
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start_agent_state = AgentState(game_context.dust_car.position, game_context.dust_car.orientation)
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start_agent_state = AgentState(game_context.dust_car.position, game_context.dust_car.orientation)
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path = find_path_to_nearest_can(start_agent_state, game_context.grid)
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path = find_path_to_nearest_can(start_agent_state, game_context.grid, game_context.city)
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if path == None or len(path) == 0:
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if path == None or len(path) == 0:
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break
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break
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move_dust_car(path, game_context)
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move_dust_car(path, game_context)
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