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Optimal dynamic incentive scheduling for Hawk-Dove evolutionary games

Stuckey, K. and Dua, R. and Ma, Y. and Parker, J. and Newton, P. K. (2022) Optimal dynamic incentive scheduling for Hawk-Dove evolutionary games. Physical Review E, 105 (1). Art. No. 014412. ISSN 2470-0045. doi:10.1103/PhysRevE.105.014412.

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The Hawk-Dove evolutionary game offers a paradigm of the trade-offs associated with aggressive and passive behaviors. When two (or more) populations of players compete, their success or failure is measured by their frequency in the population, and the system is governed by the replicator dynamics. We develop a time-dependent optimal-adaptive control theory for this dynamical system in which the entries of the payoff matrix are dynamically altered to produce control schedules that minimize and maximize the aggressive population through a finite-time cycle. These schedules provide upper and lower bounds on the outcomes for all possible strategies since they represent two extremizers of the cost function. We then adaptively extend the optimal control schedules over multiple cycles to produce absolute maximizers and minimizers for the system.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Stuckey, K.0000-0003-3435-9188
Parker, J.0000-0001-9598-2454
Newton, P. K.0000-0002-9477-0318
Additional Information:© 2022 American Physical Society. Received 21 September 2021; accepted 5 January 2022; published 21 January 2022. We gratefully acknowledge support from the Army Research Office MURI Award No. W911NF1910269.
Funding AgencyGrant Number
Army Research Office (ARO)W911NF1910269
Issue or Number:1
Record Number:CaltechAUTHORS:20210817-142931875
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110283
Deposited By: Tony Diaz
Deposited On:18 Aug 2021 22:00
Last Modified:10 Feb 2022 17:43

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