sztuczna_inteligencja_2023_.../bfs.py
2023-05-13 23:06:42 +02:00

123 lines
4.5 KiB
Python

from agentState import AgentState
from typing import Dict, Tuple
from city import City
from gridCellType import GridCellType
from agentActionType import AgentActionType
from agentOrientation import AgentOrientation
from queue import Queue
from turnCar import turn_left_orientation, turn_right_orientation
class Succ:
state: AgentState
action: AgentActionType
##cost: int
def __init__(self, state: AgentState, action: AgentActionType) -> None:
self.state = state
self.action = action
##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):
return extract_actions(currently_checked)
successors = succ(currently_checked[-1].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:
continue
if is_state_valid(s.state, grid):
new_list = currently_checked.copy()
new_list.append(s)
q.put(new_list)
return []
def extract_actions(successors: list[Succ]) -> list[AgentActionType]:
output: list[AgentActionType] = []
for s in successors:
if s.action != AgentActionType.UNKNOWN:
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))
state_succ = move_forward_succ(state)
if state_succ != None:
result.append(move_forward_succ(state))
return result
def move_forward_succ(state: AgentState) -> Succ:
position = get_next_cell(state)
if position == None:
return None
return Succ(AgentState(position, state.orientation), AgentActionType.MOVE_FORWARD)
def get_next_cell(state: AgentState) -> Tuple[int, int]:
if state.orientation == AgentOrientation.UP:
if state.position[1] - 1 < 1:
return None
return (state.position[0], state.position[1] - 1)
if state.orientation == AgentOrientation.DOWN:
if state.position[1] + 1 > 27:
return None
return (state.position[0], state.position[1] + 1)
if state.orientation == AgentOrientation.LEFT:
if state.position[0] - 1 < 1:
return None
return (state.position[0] - 1, state.position[1])
if state.position[0] + 1 > 27:
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:
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
if cell_type == GridCellType.SPEED_BUMP:
if action == AgentActionType.MOVE_FORWARD:
return 10
if action == AgentActionType.MOVE_FORWARD:
return 3
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:
return False
def _heuristics(position: Tuple[int, int], city: City):
min_distance: int = 300
found_nonvisited: bool = False
for can in city.cans:
if can.is_visited:
continue
found_nonvisited = True
distance = 3 * (abs(position[0] - can.position[0]) + abs(position[1] - can.position[1]))
if distance < min_distance:
min_distance = distance
if found_nonvisited:
return min_distance
return -1