reformatted code

DeepQLearning/main.py

@@ -13,7 +13,7 @@ marvin = dqnAgent(gamma=0.99, vareps=1.0, lr=0.001,
                   observations=nmb_of_obs, actions=nmb_of_actions, memSize=25000,
                   epsMin=0.05, bSize=16, epsDec=0.999, bins=7)
 
-rewards = [];
+rewards = []
 epsHistory = []
 avg_rewards = []
 steps = 0
@@ -21,7 +21,7 @@ verbose = False
 best_total_reward = -1000
 
 progress = tqdm(range(10000), desc='Training', unit=' episode')
-for epoche in progress:
+for epochs in progress:
     done = False
     observation = env.reset()
     observation = observation.reshape(1, -1)
@@ -61,7 +61,7 @@ for epoche in progress:
     msg += ' vareps=' + str(round(marvin.vareps, ndigits=2))
     msg += ' avg=' + str(movingAvr)
     progress.set_description(msg)
-    if epoche % 10 == 0:
+    if epochs % 10 == 0:
         np.save("eps.npy", np.array(epsHistory))
         np.save("total_rewards.npy", np.array(rewards))
         np.save("avg_rewards.npy", np.array(avg_rewards))