Using games to learn games: Game-theory representations as a source for guided social learning

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

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationSocial Robotics - 8th International Conference, ICSR 2016, Proceedings
EditorsArvin Agah, Miguel A. Salichs, Hongsheng He, John-John Cabibihan, Ayanna M. Howard
PublisherSpringer Verlag
Pages42-51
Number of pages10
ISBN (Print)9783319474366
DOIs
StatePublished - Jan 1 2016
Event8th International Conference on Social Robotics, ICSR 2016 - Kansas City, United States
Duration: Nov 1 2016Nov 3 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9979 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Social Robotics, ICSR 2016
CountryUnited States
CityKansas City
Period11/1/1611/3/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Wagner, A. (2016). Using games to learn games: Game-theory representations as a source for guided social learning. In A. Agah, M. A. Salichs, H. He, J-J. Cabibihan, & A. M. Howard (Eds.), Social Robotics - 8th International Conference, ICSR 2016, Proceedings (pp. 42-51). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9979 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-47437-3_5