def __init__(self, worldRef, pos, sigma, agentType, trueBallPos,maxPlayerSpeed, maxBallSpeed , posession = False, epsilon=0.8,alpha=0.2,discount=0.9):
agent.__init__(self, worldRef, pos, sigma, agentType, trueBallPos, maxPlayerSpeed, maxBallSpeed, posession)
#I'm using these for some stupid hand coded decisions.
#delete these when coming up with intelligent agents
#TODO: FILL as needed for qlearning
self.q_values = collections.defaultdict(int)
self.epsilon = float(epsilon) #(exploration prob)
self.alpha = float(alpha) #(learning rate)
self.discount = float(discount) #(discount rate)
#self.start = (self.startx, self.starty)
#self.end = (self.goalx, self.goaly)
self.isStochastic = True
self.isInTraining = False
self.oldState = []
self.myAction = False
self.action = "HoldBall"
self.agent_block_size = 23
self.thresh = 100
def __init__(self, env, start, discount, reward, tprob):
agent.__init__(self, env, start, discount)
def __init__(self, name, symbol, gamma_discount_factor=0.9, alpha_learning_rate=0.2, exp_rate= 0.3):
agent.__init__(self,name, symbol, gamma_discount_factor, alpha_learning_rate, exp_rate)
