only store observations in buffer when you are allowed to take an action!

torch_training/multi_agent_training.py

@@ -175,6 +175,10 @@ def main(argv):
 
             # Action
             for a in range(env.get_num_agents()):
+                if env.agents[a].speed_data['position_fraction'] == 0.:
+                    register_action_state[a] = True
+                else:
+                    register_action_state[a] = False
                 action = agent.act(agent_obs[a], eps=eps)
                 action_prob[action] += 1
                 action_dict.update({a: action})
@@ -192,7 +196,7 @@ def main(argv):
                     final_obs[a] = agent_obs[a].copy()
                     final_obs_next[a] = agent_next_obs[a].copy()
                     final_action_dict.update({a: action_dict[a]})
-                if not done[a]:
+                if not done[a] and register_action_state[a]:
                     agent.step(agent_obs[a], action_dict[a], all_rewards[a], agent_next_obs[a], done[a])
                 score += all_rewards[a] / env.get_num_agents()