title: Condition-dependent mate choice: A stochastic dynamic programming approach.
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.
authors.affiliation: Department of Biology, University of North Carolina, Chapel Hill, United States. Electronic address: alicia.frame@gmail.com.
authors.forename: Alicia M
authors.initials: AM
authors.lastname: Frame
authors.affiliation: Department of Operations and Decision Technologies, Indiana University, Kelley School of Business, United States. Electronic address: millsaf@indiana.edu.
authors.forename: Alex F
authors.initials: AF
authors.lastname: Mills
mesh_terms: D000818:Animals; D002755:Choice Behavior; D005260:Female; D008297:Male; D008962:Models, Theoretical; D012726:Sexual Behavior, Animal; D013269:Stochastic Processes
keywords: Dynamic programming; Markov decision process; Mate choice; Sexual selection