continue hfo.act(MOVE) else: state, valid_teammates = state_representer.get_representation( features, args.numTeammates) print("Valid Teammates: ", valid_teammates) if 0 in valid_teammates: q_learner.set_invalid(state, valid_teammates) if action is not None: reward = get_reward(status) reward_printer(state, action, reward) q_learner.update(state, action, reward) action = q_learner.get_action(state, valid_teammates) if action == 0: print("Action Taken: DRIBBLE \n") hfo.act(DRIBBLE) elif action == 1: print("Action Taken: SHOOT \n") hfo.act(SHOOT) elif args.numTeammates > 0: print("Action Taken: PASS -> {0} \n".format(action - 2)) hfo.act(PASS, features[15 + 6 * (action - 2)]) status = hfo.step() if action is not None and state is not None: reward = get_reward(status) reward_printer(state, action, reward)