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Destinations implemented and debugged

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Steffen Illium
2021-12-06 15:46:26 +01:00
parent 3d81b7577d
commit 7f7a3d9a3b
13 changed files with 426 additions and 76 deletions
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74
algorithms/TSP_dirt_agent.py
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@ -3,27 +3,28 @@ import numpy as np
from networkx.algorithms.approximation import traveling_salesman as tsp
from environments.factory.base.objects import Agent
from environments.factory.base.registers import FloorTiles, Actions
from environments.helpers import points_to_graph
from environments import helpers as h
from environments.helpers import Constants as c
future_planning = 7
class TSPDirtAgent(Agent):
def __init__(self, floortiles: FloorTiles, dirt_register, actions: Actions, *args,
def __init__(self, env, *args,
static_problem: bool = True, **kwargs):
super().__init__(*args, **kwargs)
self.static_problem = static_problem
self._floortiles = floortiles
self._actions = actions
self._dirt_register = dirt_register
self._floortile_graph = points_to_graph(self._floortiles.positions,
allow_euclidean_connections=self._actions.allow_diagonal_movement,
allow_manhattan_connections=self._actions.allow_square_movement)
self.local_optimization = True
self._env = env
self._floortile_graph = points_to_graph(self._env[c.FLOOR].positions,
allow_euclidean_connections=self._env._actions.allow_diagonal_movement,
allow_manhattan_connections=self._env._actions.allow_square_movement)
self._static_route = None
def predict(self, *_, **__):
if self._dirt_register.by_pos(self.pos) is not None:
if self._env[c.DIRT].by_pos(self.pos) is not None:
# Translate the action_object to an integer to have the same output as any other model
action = h.EnvActions.CLEAN_UP
elif any('door' in x.name.lower() for x in self.tile.guests):
@ -36,31 +37,50 @@ class TSPDirtAgent(Agent):
else:
action = self._predict_move()
# Translate the action_object to an integer to have the same output as any other model
action_obj = next(action_i for action_i, action_obj in enumerate(self._actions) if action_obj == action)
action_obj = next(action_i for action_i, action_obj in enumerate(self._env._actions) if action_obj == action)
return action_obj
def _predict_move(self):
if self.static_problem:
if self._static_route is None:
self._static_route = self.calculate_tsp_route()
else:
pass
next_pos = self._static_route.pop(0)
while next_pos == self.pos:
if len(self._env[c.DIRT]) >= 1:
if self.static_problem:
if not self._static_route:
self._static_route = self.calculate_tsp_route()
else:
pass
next_pos = self._static_route.pop(0)
else:
raise NotImplementedError
while next_pos == self.pos:
next_pos = self._static_route.pop(0)
else:
if not self._static_route:
self._static_route = self.calculate_tsp_route()[:7]
next_pos = self._static_route.pop(0)
while next_pos == self.pos:
next_pos = self._static_route.pop(0)
diff = np.subtract(next_pos, self.pos)
# Retrieve action based on the pos dif (like in: What do i have to do to get there?)
try:
action = next(action for action, pos_diff in h.ACTIONMAP.items()
if (diff == pos_diff).all())
except StopIteration:
print('This Should not happen!')
diff = np.subtract(next_pos, self.pos)
# Retrieve action based on the pos dif (like in: What do i have to do to get there?)
try:
action = next(action for action, pos_diff in h.ACTIONMAP.items()
if (diff == pos_diff).all())
except StopIteration:
print('This Should not happen!')
else:
action = int(np.random.randint(self._env.action_space.n))
return action
def calculate_tsp_route(self):
if self.local_optimization:
nodes = \
[self.pos] + \
[x for x in self._env[c.DIRT].positions if max(abs(np.subtract(x, self.pos))) < 3]
try:
while len(nodes) < 7:
nodes += [next(x for x in self._env[c.DIRT].positions if x not in nodes)]
except StopIteration:
nodes = [self.pos] + self._env[c.DIRT].positions
else:
nodes = [self.pos] + self._env[c.DIRT].positions
route = tsp.traveling_salesman_problem(self._floortile_graph,
nodes=[self.pos] + [x for x in self._dirt_register.positions])
nodes=nodes, cycle=True, method=tsp.greedy_tsp)
return route