def test_boltzmann():
np.random.seed(88)
beta = Parameter(0.1)
pi = Boltzmann(beta)
Q = Table((10, 3))
Q.table = np.random.randn(10, 3)
pi.set_q(Q)
s = np.array([2])
a = np.array([1])
p_s = pi(s)
p_s_test = np.array([0.30676679, 0.36223227, 0.33100094])
assert np.allclose(p_s, p_s_test)
p_sa = pi(s, a)
p_sa_test = np.array([0.36223227])
assert np.allclose(p_sa, p_sa_test)
a = pi.draw_action(s)
a_test = 2
assert a.item() == a_test
beta_2 = LinearParameter(0.2, 0.1, 2)
pi.set_beta(beta_2)
p_sa_2 = pi(s, a)
assert p_sa_2 < p_sa
pi.update(s, a)
p_sa_3 = pi(s, a)
p_sa_3_test = np.array([0.33100094])
assert np.allclose(p_sa_3, p_sa_3_test)
def test_eps_greedy():
np.random.seed(88)
eps = Parameter(0.1)
pi = EpsGreedy(eps)
Q = Table((10, 3))
Q.table = np.random.randn(10, 3)
pi.set_q(Q)
s = np.array([2])
a = np.array([1])
p_s = pi(s)
p_s_test = np.array([0.03333333, 0.93333333, 0.03333333])
assert np.allclose(p_s, p_s_test)
p_sa = pi(s, a)
p_sa_test = np.array([0.93333333])
assert np.allclose(p_sa, p_sa_test)
a = pi.draw_action(s)
a_test = 1
assert a.item() == a_test
eps_2 = LinearParameter(0.2, 0.1, 2)
pi.set_epsilon(eps_2)
p_sa_2 = pi(s, a)
assert p_sa_2 < p_sa
pi.update(s, a)
pi.update(s, a)
p_sa_3 = pi(s, a)
print(eps_2.get_value())
assert p_sa_3 == p_sa
def test_mellowmax():
np.random.seed(88)
omega = Parameter(3)
pi = Mellowmax(omega)
Q = Table((10, 3))
Q.table = np.random.randn(10, 3)
pi.set_q(Q)
s = np.array([2])
a = np.array([1])
p_s = pi(s)
p_s_test = np.array([0.08540336, 0.69215916, 0.22243748])
assert np.allclose(p_s, p_s_test)
p_sa = pi(s, a)
p_sa_test = np.array([0.69215916])
assert np.allclose(p_sa, p_sa_test)
a = pi.draw_action(s)
a_test = 2
assert a.item() == a_test
try:
beta = Parameter(0.1)
pi.set_beta(beta)
except RuntimeError:
pass
else:
assert False
try:
pi.update(s,a)
except RuntimeError:
pass
else:
assert False
