Deriving an optimally deceptive policy in two-player iterated games

Elisabeth Paulson, Booz Allen Hamilton, Christopher Griffin

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

Abstract

We formulate the problem of determining an optimally deceptive strategy in a repeated game framework. We assume that two players are engaged in repeated play. During an initial time period, Player 1 may deceptively train his opponent to expect a specific strategy. The opponent computes a best response. The best response is computed on an optimally deceptive strategy that maximizes the first player's long-run payoff during actual game play. Player 1 must take into consideration not only his real payoff but also the cost of deception. We formulate the deception problem as a nonlinear optimization problem and show how a genetic algorithm can be used to compute an optimally deceptive play. In particular, we show how the cost of deception can lead to strategies that blend a target strategy (policy) and an optimally deceptive one.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3808-3813
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

Fingerprint

Costs
Genetic algorithms

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Paulson, E., Hamilton, B. A., & Griffin, C. (2016). Deriving an optimally deceptive policy in two-player iterated games. In 2016 American Control Conference, ACC 2016 (pp. 3808-3813). [7525506] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7525506
Paulson, Elisabeth ; Hamilton, Booz Allen ; Griffin, Christopher. / Deriving an optimally deceptive policy in two-player iterated games. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3808-3813 (Proceedings of the American Control Conference).
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Paulson, E, Hamilton, BA & Griffin, C 2016, Deriving an optimally deceptive policy in two-player iterated games. in 2016 American Control Conference, ACC 2016., 7525506, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 3808-3813, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7525506

Deriving an optimally deceptive policy in two-player iterated games. / Paulson, Elisabeth; Hamilton, Booz Allen; Griffin, Christopher.

2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3808-3813 7525506 (Proceedings of the American Control Conference; Vol. 2016-July).

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

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Paulson E, Hamilton BA, Griffin C. Deriving an optimally deceptive policy in two-player iterated games. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3808-3813. 7525506. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7525506