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

Alan Wagner

doi:10.1007/978-3-319-47437-3_5

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

Alan Wagner

Aerospace Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 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 language	English (US)
Title of host publication	Social Robotics - 8th International Conference, ICSR 2016, Proceedings
Editors	Arvin Agah, Miguel A. Salichs, Hongsheng He, John-John Cabibihan, Ayanna M. Howard
Publisher	Springer Verlag
Pages	42-51
Number of pages	10
ISBN (Print)	9783319474366
DOIs	https://doi.org/10.1007/978-3-319-47437-3_5
State	Published - Jan 1 2016
Event	8th International Conference on Social Robotics, ICSR 2016 - Kansas City, United States Duration: Nov 1 2016 → Nov 3 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9979 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	8th International Conference on Social Robotics, ICSR 2016
Country/Territory	United States
City	Kansas City
Period	11/1/16 → 11/3/16

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-47437-3_5

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

Wagner, Alan. / Using games to learn games : Game-theory representations as a source for guided social learning. Social Robotics - 8th International Conference, ICSR 2016, Proceedings. editor / Arvin Agah ; Miguel A. Salichs ; Hongsheng He ; John-John Cabibihan ; Ayanna M. Howard. Springer Verlag, 2016. pp. 42-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Wagner, A 2016, Using games to learn games: Game-theory representations as a source for guided social learning. in A Agah, MA Salichs, H He, J-J Cabibihan & AM Howard (eds), Social Robotics - 8th International Conference, ICSR 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9979 LNAI, Springer Verlag, pp. 42-51, 8th International Conference on Social Robotics, ICSR 2016, Kansas City, United States, 11/1/16. https://doi.org/10.1007/978-3-319-47437-3_5

Using games to learn games : Game-theory representations as a source for guided social learning. / Wagner, Alan.

Social Robotics - 8th International Conference, ICSR 2016, Proceedings. ed. / Arvin Agah; Miguel A. Salichs; Hongsheng He; John-John Cabibihan; Ayanna M. Howard. Springer Verlag, 2016. p. 42-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9979 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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

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

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