def test_eps_greedy(self):
dqn, locals = self.create_dqn()
dqn.init()
env = locals['env']
eps = EpsilonGreedy(action_space=dqn.env_spec.action_space,
init_random_prob=0.5)
st = env.reset()
for i in range(100):
ac = eps.predict(obs=st, sess=self.sess, batch_flag=False, algo=dqn)
st_new, re, done, _ = env.step(action=ac)
self.assertTrue(env.action_space.contains(ac))
def test_eps_with_scheduler(self):
dqn, locals = self.create_dqn()
env = locals['env']
def func():
global x
return x
dqn.init()
eps = EpsilonGreedy(action_space=dqn.env_spec.action_space,
prob_scheduler=LinearScheduler(initial_p=1.0, t_fn=func, schedule_timesteps=10,
final_p=0.0),
init_random_prob=1.0)
st = env.reset()
for i in range(10):
global x
ac = eps.predict(obs=st, sess=self.sess, batch_flag=False, algo=dqn)
st_new, re, done, _ = env.step(action=ac)
self.assertAlmostEqual(eps.parameters('random_prob_func')(), 1.0 - (1.0 - 0.0) / 10 * x)
x += 1