Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Understanding intelligence
The evolution of cooperation in an ecological context: an agent based model
Dynamics in human and primate societies
Emergent patterns of mate choice in human populations
Artificial Life
KAMA: A Temperature-Driven Model of Mate Choice Using Dynamic Partner Representations
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Partner Search Heuristics in the Lab: Stability of Matchings Under Various Preference Structures
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
How to pick the right one: investigating tradeoffs among female mate choice strategies in treefrogs
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Development and evaluation of an agent-based model of sexual partnership
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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We present a conceptual framework for the study of mate choice in monogamous mating systems with non-negligible courtship time. Within this framework, we develop a mate choice model for the common case where individuals have a changing social network of potential partners. The performance and robustness of different agent strategies is evaluated, emphasizing the important role that courtship plays in mate choice. Specifically, the courtship period can be used by individuals to swap to better partners when they become available. We found that using courtship as a mechanism for holding partners before full commitment to mating provides strategic advantages relative to sequential search using aspiration levels. Moreover, simple heuristics that require little computation provide a degree of robustness to environmental (parameter) changes that is unattainable by strategies based on more extensive information processing. Our model produces realistic patterns of assortative mating (high within-couple mate value correlations) and rates of mating that match empirical data on human sexual/romantic relationships much more closely than previous accounts from biology and the social sciences.