Teach Me What You Want to Play: Learning Variants of Connect Four Through Human-Robot Interaction

Ali Ayub, Alan R. Wagner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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. (A preliminary version of this paper was accepted at[5]).

Original languageEnglish (US)
Title of host publicationSocial Robotics - 12th International Conference, ICSR 2020, Proceedings
EditorsAlan R. Wagner, David Feil-Seifer, Kerstin S. Haring, Silvia Rossi, Thomas Williams, Hongsheng He, Shuzhi Sam Ge
PublisherSpringer Science and Business Media Deutschland GmbH
Pages502-515
Number of pages14
ISBN (Print)9783030620554
DOIs
StatePublished - 2020
Event12th International Conference on Social Robotics, ICSR 2020 - Golden, United States
Duration: Nov 14 2020Nov 18 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12483 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Social Robotics, ICSR 2020
CountryUnited States
CityGolden
Period11/14/2011/18/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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