Files
DeepRL/policy.py
T

23 lines
851 B
Python

#######################################################################
# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #
# Permission given to modify the code as long as you keep this #
# declaration at the top #
#######################################################################
import numpy as np
class GreedyPolicy:
def __init__(self, epsilon, decay_factor, min_epsilon):
self.epsilon = epsilon
self.decay_factor = decay_factor
self.min_epsilon = min_epsilon
def sample(self, state):
if np.random.rand() < self.epsilon:
return np.random.randint(0, len(state))
return np.argmax(state)
def update_epsilon(self):
if self.epsilon > self.min_epsilon:
self.epsilon *= self.decay_factor