论文标题
人工代理应该在人类机器人协作解决问题方面寻求帮助吗？
Should artificial agents ask for help in human-robot collaborative problem-solving?
论文作者
论文摘要
尽可能快地转移我们的大脑到人工智能是一个雄心勃勃的目标，它将有助于在AI和机器人技术中提高最新技术。从这个角度来看，我们建议从人类机器人相互作用中的经验研究中得出的假设开始，并验证它们是否以儿童与基本强化学习算法相同的方式验证。因此，我们检查在解决简单的封闭式任务（Hanoï的塔）时是否从专家那里获得帮助，可以根据播放器是规范或要求的，可以加速学习此任务。我们的经验使我们得出结论，无论是否要求，Q学习算法的好处与儿童的专家帮助一样。
Transferring as fast as possible the functioning of our brain to artificial intelligence is an ambitious goal that would help advance the state of the art in AI and robotics. It is in this perspective that we propose to start from hypotheses derived from an empirical study in a human-robot interaction and to verify if they are validated in the same way for children as for a basic reinforcement learning algorithm. Thus, we check whether receiving help from an expert when solving a simple close-ended task (the Towers of Hanoï) allows to accelerate or not the learning of this task, depending on whether the intervention is canonical or requested by the player. Our experiences have allowed us to conclude that, whether requested or not, a Q-learning algorithm benefits in the same way from expert help as children do.
