updated training file

torch_training/training_navigation.py

@@ -146,6 +146,9 @@ for trials in range(1, n_trials + 1):
         distance = norm_obs_clip(distance)
         agent_data = np.clip(agent_data, -1, 1)
         obs[a] = np.concatenate((np.concatenate((data, distance)), agent_data))
+        agent_data = env.agents[a]
+        speed = 1 #np.random.randint(1,5)
+        agent_data.speed_data['speed'] = 1. / speed
 
     for i in range(2):
         time_obs.append(obs)
@@ -153,6 +156,7 @@ for trials in range(1, n_trials + 1):
     for a in range(env.get_num_agents()):
         agent_obs[a] = np.concatenate((time_obs[0][a], time_obs[1][a]))
 
+
     score = 0
     env_done = 0
     # Run episode
@@ -167,7 +171,7 @@ for trials in range(1, n_trials + 1):
             if demo:
                 eps = 0
             # action = agent.act(np.array(obs[a]), eps=eps)
-            action = 2 #agent.act(agent_obs[a], eps=eps)
+            action = agent.act(agent_obs[a], eps=eps)
             action_prob[action] += 1
             action_dict.update({a: action})
         # Environment step