教我你想玩什么：通过人机交互学习Connect Four的变体
Teach Me What You Want to Play: Learning Variants of Connect Four through Human-Robot Interaction
摘要：
本文研究了如何使用博弈论表示来表示和学习如何玩互动游戏，如连接四。我们结合了学习的演示，主动学习和游戏理论，允许机器人利用其发展中的代表性的游戏进行问答会话与一个人，从而填补其知识的空白。本文演示了一种方法，用于教机器人的游戏连接四个及其变体的获胜条件，使用一个单一的演示和几个试验的例子与问答会议由机器人领导。我们的研究结果表明，机器人可以学习任意的获胜条件的游戏，几乎没有先验知识的获胜条件，然后玩游戏与人类利用学习的获胜条件。我们的实验还表明，一些问题是更重要的学习游戏的获胜条件。我们相信这种方法可以广泛应用于各种互动学习场景。
英文摘要：
This paper investigates the use of game theoretic representations to represent and learn how to play interactive games such as Connect Four. We combine aspects of learning by demonstration, active learning, and game theory allowing a robot to leverage its developing representation of the game to conduct question/answer sessions with a person, thus filling in gaps in its knowledge. The paper demonstrates a method for teaching a robot the win conditions of the game Connect Four and its variants using a single demonstration and a few trial examples with a question and answer session led by the robot. Our results show that the robot can learn arbitrary win conditions for the game with little prior knowledge of the win conditions and then play the game with a human utilizing the learned win conditions. Our experiments also show that some questions are more important for learning the game's win conditions. We believe that this method could be broadly applied to a variety of interactive learning scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
