def __init__(self, agent_id, ally_ids, enemy_ids):
"""Extend the constructor from the PacmanAgent superclass.
Args:
agent_id: The identifier of an agent.
ally_ids: The identifier of all allies agents.
enemy_ids: The identifier of all enemies agents.
"""
super(EaterPacmanAgent, self).__init__(agent_id, ally_ids, enemy_ids)
self.eat_behavior = behaviors.EatBehavior()
def __init__(self, agent_id, ally_ids, enemy_ids):
"""Constructor for the BehaviorLearningPacmanAgent.
Extend the PacmanAgent constructor.
Setup the features the pacman will use, the behaviors, the explotation
and exploration rate, initialize a QLearningWithApproximation object
initialize behavior count and set test mode to 'False'.
Args:
agent_id: The identifier of the agent.
ally_ids: The identifiers of all the allies.
enemy_ids: The identifiers of all the enemies.
"""
super(BehaviorLearningPacmanAgent,
self).__init__(agent_id, ally_ids, enemy_ids)
self.features = [features.FoodDistanceFeature()]
for enemy_id in enemy_ids:
self.features.append(features.EnemyDistanceFeature(enemy_id))
for id_ in [agent_id] + ally_ids + enemy_ids:
self.features.append(features.FragileAgentFeature(id_))
self.behaviors = [
behaviors.EatBehavior(),
behaviors.FleeBehavior(),
behaviors.SeekBehavior(),
behaviors.PursueBehavior()
]
self.K = 1.0 # Learning rate
self.exploration_rate = 0.1
QLearning = learning.QLearningWithApproximation
self.learning = QLearning(learning_rate=0.1,
discount_factor=0.9,
actions=self.behaviors,
features=self.features,
exploration_rate=self.exploration_rate)
self.previous_behavior = self.behaviors[0]
self.behavior_count = {}
self.reset_behavior_count()
self.test_mode = False
def __init__(self, agent_id, ally_ids, enemy_ids):
super(BehaviorLearningPacmanAgent, self).__init__(agent_id, ally_ids, enemy_ids)
self.features = [features.FoodDistanceFeature()]
for enemy_id in enemy_ids:
self.features.append(features.EnemyDistanceFeature(enemy_id))
for id_ in [agent_id] + ally_ids + enemy_ids:
self.features.append(features.FragileAgentFeature(id_))
self.behaviors = [behaviors.EatBehavior(), behaviors.FleeBehavior(),
behaviors.SeekBehavior(), behaviors.PursueBehavior()]
self.K = 1.0 # Learning rate
self.exploration_rate = 0.1
self.learning = learning.QLearningWithApproximation(learning_rate=0.1,
discount_factor=0.9, actions=self.behaviors, features=self.features,
exploration_rate=self.exploration_rate)
self.previous_behavior = self.behaviors[0]
self.behavior_count = {}
self.reset_behavior_count()
self.test_mode = False
def __init__(self, agent_id, ally_ids, enemy_ids):
super(EaterPacmanAgent, self).__init__(agent_id, ally_ids, enemy_ids)
self.eat_behavior = behaviors.EatBehavior()