improved plot

k-bandits.py

@@ -45,15 +45,15 @@ def test(episode_len: int, epsilon: float, qu: np.array, nu: np.array, bandit: C
 
 if __name__ == '__main__':
 
-	epsilon = 0.1		# Anti-greediness
-	rho = 0.01		# reduce epsilon with age
+	epsilon = 0.5		# Anti-greediness
+	rho = 0.005		# reduce epsilon with age
 
 	# init bandits with different biases for shifting reward probability
 	# -> expected reward q*(a)
 	ql_star = np.array([-0.4, -0.3, -0.2, -0.1, 0.0, +0.1, +0.2, +0.3, +0.4, +0.5])
 
 	num_realisations = 10
-	episode_len = 1000
+	episode_len = 10000
 	r_mean = np.zeros(episode_len)
 	for age in range(0, num_realisations):
 		# Init Q and N
@@ -68,4 +68,8 @@ if __name__ == '__main__':
 
 	pl.plot(r_mean/num_realisations)
 	pl.grid()
+	ax = pl.gca()
+	ax.set_xlim([-episode_len/10, episode_len])
+	ax.set_ylim([0, 1])
+
 	pl.show()