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sztuczna_inteligencja_2023_smieciarka
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dodany A* - coś jeszcze nie działa

This commit is contained in:
majkellll 2023-05-15 08:07:08 +02:00
parent dd34b7341a
commit 5440626353
4 changed files with 79 additions and 57 deletions
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97
bfs.py
View File

@ -1,49 +1,58 @@
from agentState import AgentState
from typing import Dict, Tuple
from typing import Dict, Tuple, List, Set
from city import City
from gridCellType import GridCellType
from agentActionType import AgentActionType
from agentOrientation import AgentOrientation
from queue import Queue
from queue import PriorityQueue
from turnCar import turn_left_orientation, turn_right_orientation
import heapq
class Succ:
state: AgentState
action: AgentActionType
##cost: int
cost: int
def __init__(self, state: AgentState, action: AgentActionType) -> None:
def __init__(self, state: AgentState, action: AgentActionType, cost: int) -> None:
self.state = state
self.action = action
##self.cost = cost
self.cost = cost
def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> list[AgentActionType]:
q: Queue[list[Succ]] = Queue()
visited: list[AgentState] = []
startStates: list[Succ] = [Succ(startState, AgentActionType.UNKNOWN)]
q.put(startStates)
while not q.empty():
currently_checked = q.get()
visited.append(currently_checked[-1].state)
if is_state_success(currently_checked[-1].state, grid):
def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[AgentActionType]:
pq: PriorityQueue[Tuple[int, List[Succ]]] = PriorityQueue()
visited: set[AgentState] = set()
startStates: list[Succ] = [Succ(startState, AgentActionType.UNKNOWN, 0)]
pq.put((0, startStates))
while not pq.empty():
_, currently_checked = pq.get()
last_state = currently_checked[-1].state
if last_state in visited:
continue
visited.add(last_state)
if is_state_success(last_state, grid):
return extract_actions(currently_checked)
successors = succ(currently_checked[-1].state)
successors = succ(last_state)
for s in successors:
already_visited = False
for v in visited:
if v.position[0] == s.state.position[0] and v.position[1] == s.state.position[1] and s.state.orientation == v.orientation:
already_visited = True
break
if already_visited:
if s.state in visited:
continue
if is_state_valid(s.state, grid):
new_list = currently_checked.copy()
new_list.append(s)
q.put(new_list)
if not is_state_valid(s.state, grid):
continue
g_cost = currently_checked[-1].cost + get_cost_for_action(s.action, grid.get(s.state.position, GridCellType.STREET_HORIZONTAL))
h_cost = _heuristics(s.state.position, city)
f_cost = g_cost + h_cost
new_list = currently_checked.copy()
new_list.append(s)
pq.put((f_cost, new_list))
return []
def extract_actions(successors: list[Succ]) -> list[AgentActionType]:
output: list[AgentActionType] = []
for s in successors:
@ -51,20 +60,23 @@ def extract_actions(successors: list[Succ]) -> list[AgentActionType]:
output.append(s.action)
return output
def succ(state: AgentState) -> list[Succ]:
result: list[Succ] = []
result.append(Succ(AgentState(state.position, turn_left_orientation(state.orientation)), AgentActionType.TURN_LEFT))
result.append(Succ(AgentState(state.position, turn_right_orientation(state.orientation)), AgentActionType.TURN_RIGHT))
result.append(Succ(AgentState(state.position, turn_left_orientation(state.orientation)), AgentActionType.TURN_LEFT, 0))
result.append(Succ(AgentState(state.position, turn_right_orientation(state.orientation)), AgentActionType.TURN_RIGHT, 0))
state_succ = move_forward_succ(state)
if state_succ != None:
result.append(move_forward_succ(state))
if state_succ is not None:
result.append(Succ(state_succ.state, AgentActionType.MOVE_FORWARD, state_succ.cost))
return result
def move_forward_succ(state: AgentState) -> Succ:
position = get_next_cell(state)
if position == None:
if position is None:
return None
return Succ(AgentState(position, state.orientation), AgentActionType.MOVE_FORWARD)
return Succ(AgentState(position, state.orientation), AgentActionType.MOVE_FORWARD,
get_cost_for_action(AgentActionType.MOVE_FORWARD, GridCellType.STREET_HORIZONTAL))
def get_next_cell(state: AgentState) -> Tuple[int, int]:
@ -84,13 +96,15 @@ def get_next_cell(state: AgentState) -> Tuple[int, int]:
return None
return (state.position[0] + 1, state.position[1])
def is_state_success(state: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> bool:
next_cell = get_next_cell(state)
try:
return grid[next_cell] == GridCellType.GARBAGE_CAN
except:
except KeyError:
return False
def get_cost_for_action(action: AgentActionType, cell_type: GridCellType) -> int:
if action == AgentActionType.TURN_LEFT or action == AgentActionType.TURN_RIGHT:
return 1
@ -102,12 +116,14 @@ def get_cost_for_action(action: AgentActionType, cell_type: GridCellType) -> int
def is_state_valid(state: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> bool:
try:
return grid[state.position] == GridCellType.STREET_HORIZONTAL or grid[state.position] == GridCellType.STREET_VERTICAL or grid[state.position] == GridCellType.SPEED_BUMP
except:
try:
return grid[state.position] == GridCellType.STREET_HORIZONTAL or grid[
state.position] == GridCellType.STREET_VERTICAL or grid[state.position] == GridCellType.SPEED_BUMP
except KeyError:
return False
def _heuristics(position: Tuple[int, int], city: City):
def _heuristics(position: Tuple[int, int], city: City) -> int:
min_distance: int = 300
found_nonvisited: bool = False
for can in city.cans:
@ -120,4 +136,5 @@ def _heuristics(position: Tuple[int, int], city: City):
if found_nonvisited:
return min_distance
return -1

15
city.py
View File

@ -2,8 +2,9 @@ from typing import List, Dict, Tuple
from garbageCan import GarbageCan
from speedBump import SpeedBump
from street import Street
from gameContext import GameContext
from gameContext import GameContext
class City:
cans: List[GarbageCan]
bumps: List[SpeedBump]
@ -18,10 +19,10 @@ class City:
def add_can(self, can: GarbageCan) -> None:
self.nodes.append(can)
self.cans_dict[can.position] = can
def add_street(self, street: Street) -> None:
self.streets.append(street)
def add_bump(self, bump: SpeedBump) -> None:
self.streets.append(bump)
@ -33,11 +34,11 @@ class City:
def _render_streets(self, game_context: GameContext) -> None:
for street in self.streets:
street.render(game_context)
def _render_nodes(self, game_context: GameContext) -> None:
for node in self.nodes:
node.render(game_context)
def _render_bumps(self, game_context: GameContext) -> None:
for bump in self.bumps:
bump.render(game_context)
bump.render(game_context)

7
main.py
View File

@ -1,4 +1,6 @@
import pygame
from city import City
from gameEventHandler import handle_game_event
from gameContext import GameContext
from startup import startup
@ -17,8 +19,11 @@ game_context = GameContext()
game_context.dust_car_pil = dust_car_pil
game_context.dust_car_pygame = pygame.image.frombuffer(dust_car_pil.tobytes(), dust_car_pil.size, 'RGB')
game_context.canvas = canvas
city = City()
startup(game_context)
collect_garbage(game_context)
collect_garbage(game_context, city)
exit = False

17
movement.py
View File

@ -9,19 +9,21 @@ from agentOrientation import AgentOrientation
import pygame
from bfs import find_path_to_nearest_can
from agentState import AgentState
from city import City
def collect_garbage(game_context: GameContext) -> None:
def collect_garbage(game_context: GameContext, city: City) -> None:
while True:
start_agent_state = AgentState(game_context.dust_car.position, game_context.dust_car.orientation)
path = find_path_to_nearest_can(start_agent_state, game_context.grid)
if path == None or len(path) == 0:
path = find_path_to_nearest_can(start_agent_state, game_context.grid, city)
if path is None or len(path) == 0:
break
move_dust_car(path, game_context)
next_position = calculate_next_position(game_context.dust_car)
game_context.grid[next_position] = GridCellType.VISITED_GARBAGE_CAN
game_context.city.cans_dict[next_position].is_visited = True
pass
def move_dust_car(actions: list[AgentActionType], game_context: GameContext) -> None:
for action in actions:
street_position = game_context.dust_car.position
@ -39,12 +41,9 @@ def move_dust_car(actions: list[AgentActionType], game_context: GameContext) ->
game_context.render_in_cell(street_position, "imgs/street_horizontal.png")
elif game_context.grid[street_position] == GridCellType.STREET_VERTICAL:
game_context.render_in_cell(street_position, "imgs/street_vertical.png")
elif game_context.grid[street_position] == GridCellType.SPEED_BUMP:
game_context.render_in_cell(street_position, "imgs/speed_bump.png")
pygame.display.update()
time.sleep(0.15)
time.sleep(0.5)
def calculate_next_position(car: GarbageTruck) -> Tuple[int, int]:
if car.orientation == AgentOrientation.UP:
@ -61,4 +60,4 @@ def calculate_next_position(car: GarbageTruck) -> Tuple[int, int]:
return (car.position[0] - 1, car.position[1])
if car.position[0] + 1 > 27:
return None
return (car.position[0] + 1, car.position[1])
return (car.position[0] + 1, car.position[1])