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Condition-dependent mate choice: A stochastic dynamic programming approach

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  • Frame, Alicia M.
  • Mills, Alex F.

Abstract

We study how changing female condition during the mating season and condition-dependent search costs impact female mate choice, and what strategies a female could employ in choosing mates to maximize her own fitness. We address this problem via a stochastic dynamic programming model of mate choice. In the model, a female encounters males sequentially and must choose whether to mate or continue searching. As the female searches, her own condition changes stochastically, and she incurs condition-dependent search costs. The female attempts to maximize the quality of the offspring, which is a function of the female’s condition at mating and the quality of the male with whom she mates. The mating strategy that maximizes the female’s net expected reward is a quality threshold. We compare the optimal policy with other well-known mate choice strategies, and we use simulations to examine how well the optimal policy fares under imperfect information.

Suggested Citation

  • Frame, Alicia M. & Mills, Alex F., 2014. "Condition-dependent mate choice: A stochastic dynamic programming approach," Theoretical Population Biology, Elsevier, vol. 96(C), pages 1-7.
    • Handle: RePEc:eee:thpobi:v:96:y:2014:i:c:p:1-7
    DOI: 10.1016/j.tpb.2014.06.001
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    References listed on IDEAS

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    1. Edmund J. Collins & John M. McNamara & David M. Ramsey, 2006. "Learning rules for optimal selection in a varying environment: mate choice revisited," Behavioral Ecology, International Society for Behavioral Ecology, vol. 17(5), pages 799-809, September.
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