Endogenous regulation of selection pressure : a minimal game-theoretical model

Gašperov, Bruno (author), Šter, Branko (author)

Selection pressure, determining which individuals survive and reproduce, is traditionally regarded as an exogenous property of the environment. However, growing evidence from the Extended Evolutionary Synthesis (EES) suggests that the strength of selection can, to some extent, be modulated by the organisms themselves. In this paper, we propose a minimal game-theoretical model that formalizes the concept of endogenous selection pressure. In the model, individuals collectively determine the intensity of selection through their actions: each agent ‘‘votes’’ to either intensify or relax selection depending on its relative fitness rank. The aggregate outcome of these decisions defines the number of reproducers, k, which is inversely related to the overall strength of selection. We analytically derive all pure strategy Nash equilibria of the game and examine their properties. By internalizing selection as a population-level emergent variable, the framework provides a tractable formalization of key principles from the EES and offers a foundation for exploring evolutionary dynamics that arise under the presence of endogenous selection pressure.

• Language: English
• Keywords: selection pressure, game theory, extended evolutionary synthesis, self-adaptation
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: 7 str.
• Numbering: Vol. 259, art. 105666
• PID: 20.500.12556/RUL-177410
• UDC: 004
• ISSN on article: 0303-2647
• DOI: 10.1016/j.biosystems.2025.105666
• COBISS.SI-ID: 262193923
• Publication date in RUL: 23.12.2025

Record is a part of a journal

• Title: Biosystems
• Shortened title: Biosystems
• Publisher: Elsevier
• ISSN: 0303-2647
• COBISS.SI-ID: 25103360

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: selekcijski pritisk, teorija iger, razširjena evolucijska sinteza, samoadaptacija

Projects

• Funder: EC - European Commission
• Funding programme: HE
• Project number: 101081355
• Name: Machine learning for Sciences and Humanities
• Acronym: SMASH

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P2-0241
• Name: Sinergetika kompleksnih sistemov in procesov