def register_initial_state(self, game_state):
self.start = game_state.get_agent_position(self.index)
CaptureAgent.register_initial_state(self, game_state)
if self.inference_initializer:
self.inferences[:] = [
ExactInference(opponent, self.distancer, game_state)
for opponent in self.get_opponents(game_state)
]
def register_initial_state(self, game_state):
self.start = game_state.get_agent_position(self.index)
CaptureAgent.register_initial_state(self, game_state)
#two things which will be useful for future calculations
self.mid_screen = game_state.data.layout.width/2
self.legal_positions = [p for p in game_state.get_walls().as_list(False) if p[1] > 1]
#used for probabilistic tracking
if self.inference_initializer:
self.inferences[:] = [ExactInference(opponent, self.distancer, game_state)
for opponent in self.get_opponents(game_state)]
def register_initial_state(self, game_state):
"""Handle initial setup of the agent to populate useful fields.
Useful fields include things such as what team we're on.
A distance_calculator instance caches the maze distances
between each pair of positions, so your agents can use:
self.distancer.get_distance(p1, p2)
"""
self.start = game_state.get_agent_position(self.index)
CaptureAgent.register_initial_state(self, game_state)
def register_initial_state(self, game_state):
"""Handle initial setup of the agent to populate useful fields.
Useful fields include things such as what team we're on.
A distance_calculator instance caches the maze distances
between each pair of positions, so your agents can use:
self.distancer.get_distance(p1, p2)
IMPORTANT: This method may run for at most 15 seconds.
"""
# Make sure you do not delete the following line. If you would like to
# use Manhattan distances instead of maze distances in order to save
# on initialization time, please take a look at
# CaptureAgent.register_initial_state in capture_agents.py.
CaptureAgent.register_initial_state(self, game_state)
def register_initial_state(self, game_state):
"""
This method handles the initial setup of the
agent to populate useful fields (such as what team
we're on).
A distanceCalculator instance caches the maze distances
between each pair of positions, so your agents can use:
self.distancer.getDistance(p1, p2)
IMPORTANT: This method may run for at most 15 seconds.
"""
'''
Make sure you do not delete the following line. If you would like to
use Manhattan distances instead of maze distances in order to save
on initialization time, please take a look at
CaptureAgent.register_initial_state in captureAgents.py.
'''
CaptureAgent.register_initial_state(self, game_state)
'''
Your initialization code goes here, if you need any.
'''
self.behaviour_state = 'Guard'
self.set_center(game_state)
self.eaten_food = 0
self.prev_food_state = self.get_food_you_are_defending(game_state)
self.opponent_indices = self.get_opponents(game_state)
self.team_indices = self.get_team(game_state)
self.teammate_index = self.get_team(game_state)[:]
self.teammate_index.remove(self.index)
self.defence_destination = None
self.attack_destination = None
self.opponent_positions = {}
self.opponent_previous_positions = {}
self.opponent_detected = None
for opponent_index in self.opponent_indices:
self.opponent_positions[opponent_index] = None
self.opponent_previous_positions[opponent_index] = None
self.set_guard_mode()
def __init__(self, index, inferences, inference_initializer=False):
self.inferences = inferences
self.inference_initializer = inference_initializer
CaptureAgent.__init__(self, index)
def register_initial_state(self, game_state):
self.start = game_state.get_agent_position(self.index)
CaptureAgent.register_initial_state(self, game_state)