 Evolution and the ultimatum game: An agent-based model with interbirth intervals and population structureJeffrey C Schank and Matt L Miller PLOS Computational Biology, 2026, vol. 22, issue 6, 1-35 Abstract: The ultimatum game (UG) is widely used to study mutually beneficial exchanges, fairness, and prosocial behavior across different societies. However, human behavior in UG experiments does not align with the game-theoretical prediction that proposers should offer the least positive amount and responders should accept such offers. Instead, proposers make generous offers that are greater than the minimum responders are willing to accept, resulting in generous offers with wide offer-acceptance gaps. Numerous evolutionary models of the UG have been created and studied to explain human behavior, particularly generous offers made in UG experiments. These models have recently faced criticism for lacking biological realism and not adequately explaining the data. Here, we present an agent-based model inspired by our hunter-gatherer ancestors and with a biologically more realistic selection process. We assume that (1) agents exist in group-structured and group-clustered populations, where reproduction (2) depends on resource accumulation, but (3) is limited by interbirth intervals. We ran simulations to assess whether this biologically more realistic model evolves patterns of behavior consistent with patterns in the data from meta-analyses of human behavior in the UG. For the proposed model, we show that generous offers robustly evolve, as well as the difficult-to-explain offer-acceptance gaps, only in group-structured populations with interbirth intervals. We demonstrate that these results are robust and may help explain variation in data across societies. We discuss how interbirth intervals interact with group structure to modulate offer and rejection costs, favoring the evolution of generous offers, offer-acceptance gaps, and other patterns in the data on human behavior in the UG. We also discuss why weak selection and/or high mutation rate models cannot explain all the patterns in UG experimental data. We discuss biological realism and conclude that group structure and interbirth intervals may be essential for explaining prosocial behavior across societies.Author summary: We used an agent-based model to investigate why people consistently make generous offers in the ultimatum game, contradicting classic game-theoretical predictions that proposers should offer the minimum possible and responders should accept any positive offer. Previous evolutionary models attempting to explain this generosity have been criticized for being biologically unrealistic. In response, our agent-based model reflects early human evolutionary conditions, incorporating group-structured populations, reproduction based on resource accumulation, and natural limitations on interbirth intervals (birth frequency). Our simulations show that generous offers and significant gaps between what is offered and what would be accepted evolve under these conditions, aligning with patterns found in real-world experimental data from different societies. Crucially, our model reveals that group structure and limits on the rate of reproduction interact to favor the evolution of generosity. We argue that these features are necessary for explaining cross-cultural variations in generosity, outperforming less realistic models relying only on weak selection or high mutation rates. Date: 2026 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1014387 DOI: 10.1371/journal.pcbi.1014387 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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