def next_action(self, percept, random_generator):
if {"x": 0, "y": 0, "looks_like": "dirt"} in percept["entities"]:
return PickUp()
targets = set()
obstructions = set()
for key in self.passable:
coords = key[1:-1].split(",")
x = int(coords[0])
y = int(coords[1])
if self.passable[key]:
for pos in [(x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)]:
if str(pos) not in self.passable:
targets.add(pos)
else:
obstructions.add((x, y))
if not targets:
return DoNothing()
my_x = percept["position"]["x"]
my_y = percept["position"]["y"]
problem = PathfindingProblem((my_x, my_y), targets, obstructions, [])
try:
plan = a_star_graph(problem, get_heuristic(problem))
return Move(direction=plan[0])
except NoSolutionError:
return DoNothing()
def next_action(self, percept, random_generator):
if {"x": 0, "y": 0, "looks_like": "dirt"} in percept["entities"]:
return PickUp()
if percept["position"]["x"] == 1 and not self.moved:
return Move(direction="right")
if percept["position"]["x"] == 2 and not self.moved:
return Move(direction="left")
return DoNothing()
def next_action(self, percept, random_generator):
dirt_count = len(
[e for e in percept["entities"] if e["looks_like"] == "dirt"])
if {"x": 0, "y": 0, "looks_like": "dirt"} in percept["entities"]:
return PickUp()
if percept["position"]["x"] == 1 and dirt_count > 0:
return Move(direction="right")
if percept["position"]["x"] == 2 and dirt_count > 0:
return Move(direction="left")
return DoNothing()
def test_vanish_pickup():
system = PickUpSystem()
pickupper_components = {"pickupper": Pickupper(mode="action")}
inventory_components = {}
actions = {"pickupper": PickUp()}
position_components = PositionDict({
"pickupper": Position(x=0, y=0),
"item": Position(x=0, y=0)
})
pickup_components = {"item": VanishPickup(kind="vanish")}
score_components = {}
removed_entities = system.pick_up_items(
pickupper_components, actions, position_components,
pickup_components, score_components, inventory_components)
assert removed_entities == set(["item"])
def test_pickup_item():
system = PickUpSystem()
pickupper_components = {"pickupper": Pickupper(mode="action")}
inventory_components = {"pickupper": Inventory()}
actions = {"pickupper": PickUp()}
position_components = PositionDict({
"pickupper": Position(x=0, y=0),
"item": Position(x=0, y=0)
})
pickup_components = {"item": ItemPickup(kind="item")}
score_components = {}
removed_entities = system.pick_up_items(
pickupper_components, actions, position_components,
pickup_components, score_components, inventory_components)
assert inventory_components["pickupper"] == Inventory(items=["item"])
assert "item" not in position_components
assert removed_entities == set()
def next_action(self, percept, random_generator):
if (self.manual_pickup and {"x": 0, "y": 0, "looks_like": "coin"}
in percept["entities"]):
return PickUp()
walls = [(e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "wall"]
coins = [(e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "coin"]
if not coins:
return DoNothing()
problem = PathfindingProblem((0, 0), coins, walls, [])
try:
plan = a_star_graph(problem, get_heuristic(problem))
return Move(direction=plan[0])
except NoSolutionError:
return DoNothing()
def next_action(self, percept, random_generator):
if not self.plan:
return DoNothing()
# Parse percept
missionaries = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "coin")
cannibals = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "evilCoin")
grass = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "grass")
dirt = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "dirt")
empty_shore = (grass | dirt) - missionaries - cannibals
walls = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "wall")
water = set((e["x"], e["y"]) for e in percept["entities"]
if e["looks_like"] == "water")
goal = self.plan[0]
# First, ensure inventory is correct
too_many_missionaries = percept["inventory"].count(
"coin") > goal.missionaries
too_many_cannibals = percept["inventory"].count(
"evilCoin") > goal.cannibals
if too_many_missionaries or too_many_cannibals:
if (0, 0) in empty_shore:
if too_many_missionaries:
return Drop(index=percept["inventory"].index("coin"))
if too_many_cannibals:
return Drop(index=percept["inventory"].index("evilCoin"))
problem = PathfindingProblem((0, 0), empty_shore, walls | water,
[])
return Move(
direction=a_star_graph(problem, get_heuristic(problem))[0])
too_few_missionaries = percept["inventory"].count(
"coin") < goal.missionaries
if too_few_missionaries:
if (0, 0) in missionaries:
return PickUp()
problem = PathfindingProblem((0, 0), missionaries, walls | water,
[])
return Move(
direction=a_star_graph(problem, get_heuristic(problem))[0])
too_few_cannibals = percept["inventory"].count(
"evilCoin") < goal.cannibals
if too_few_cannibals:
if (0, 0) in cannibals:
return PickUp()
problem = PathfindingProblem((0, 0), cannibals, walls | water, [])
return Move(
direction=a_star_graph(problem, get_heuristic(problem))[0])
# Then, go to the correct shore
if goal.destination == "dirt":
problem = PathfindingProblem((0, 0), dirt, walls, [])
return Move(
direction=a_star_graph(problem, get_heuristic(problem))[0])
else:
problem = PathfindingProblem((0, 0), grass, walls, [])
return Move(
direction=a_star_graph(problem, get_heuristic(problem))[0])
def next_action(self, percept, random_generator):
if {"x": 0, "y": 0, "looks_like": "dirt"} in percept["entities"]:
return PickUp()
direction = random_generator.choice(["up", "down", "left", "right"])
return Move(direction=direction)