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Using Games to Learn Games: Game-Theory Representations as a Source for Guided Social Learning

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Social Robotics (ICSR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9979))

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Abstract

This paper examines the use of game-theoretic representations as a means of representing and learning both interactive games and patterns of interaction in general between a human and a robot. The paper explores the means by which a robot could generate the structure of a game. In addition to offering the formal underpinnings necessary for reasoning about strategy, game theory affords a method for representing the interactive structure of a game computationally. We investigate the possibility of teaching a robot the structure of a game via instructions, question and answer sessions led by the robot, and a mix of instruction and question and answer. Our results demonstrate that the use of game-theoretic representations may offer new advantages in terms of guided social learning.

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Author information

Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, Georgia, USA

    Alan Wagner

  2. Pennsylvania State University, State College, Pennsylvania, USA

    Alan Wagner

Authors
  1. Alan Wagner
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Correspondence to Alan Wagner .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, The University of Kansas, Lawrence, Indiana, USA

    Arvin Agah

  2. Department of Mechanical Engineering, Qatar University, Doha, Qatar

    John-John Cabibihan

  3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA

    Ayanna M. Howard

  4. Department of Systems Engineering and Automation, University Carlos III de Madrid, madrid, Spain

    Miguel A. Salichs

  5. Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, USA

    Hongsheng He

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Wagner, A. (2016). Using Games to Learn Games: Game-Theory Representations as a Source for Guided Social Learning. In: Agah, A., Cabibihan, JJ., Howard, A., Salichs, M., He, H. (eds) Social Robotics. ICSR 2016. Lecture Notes in Computer Science(), vol 9979. Springer, Cham. https://doi.org/10.1007/978-3-319-47437-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-47437-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47436-6

  • Online ISBN: 978-3-319-47437-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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