Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A general technique for computing evolutionarily stable strategies based on errors in decision-making

J M McNamara1, J N Webb, E J Collins

  • 1School of Mathematics, University of Bristol, University Walk, Bristol, BS8 1TW, UK. John.McNamara@bristol.ac.uk

Journal of Theoretical Biology
|February 28, 1998
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mixed species flocking of tits (Parus spp.): a field experiment.

Oecologia·2017
Same author

The evolution of cooperation by negotiation in a noisy world.

Journal of evolutionary biology·2016
Same author

An adaptive response to uncertainty can lead to weight gain during dieting attempts.

Evolution, medicine, and public health·2016
Same author

Isokinetic Evaluation Following Leg Injuries.

The Physician and sportsmedicine·2016
Same author

A dynamic framework for the study of optimal birth intervals reveals the importance of sibling competition and mortality risks.

Journal of evolutionary biology·2015
Same author

An infrared motion detector system for lossless real-time monitoring of animal preference tests.

Acta biologica Hungarica·2014
Same journal

The male-biased sex ratio in humans and its role in the transition from promiscuity to pair bonding.

Journal of theoretical biology·2026
Same journal

Quantifying the counter-intuitive effects of vaccination by coupling the transmission dynamics of COVID-19 and the evolution of human behaviors.

Journal of theoretical biology·2026
Same journal

An integrative model of FGF2-induced signaling and muscle cell proliferation.

Journal of theoretical biology·2026
Same journal

A hybrid reaction-diffusion and mechanical stimulus model for mandibular bone remodeling under chewing and vibratory loading.

Journal of theoretical biology·2026
Same journal

Integrated tick management strategies in fragmented peridomestic environments.

Journal of theoretical biology·2026
Same journal

Joint likelihood-free inference of the number of selected single nucleotide polymorphisms and their selection coefficients in an evolving population.

Journal of theoretical biology·2026
See all related articles

This study introduces a novel computational method for analyzing animal contests, improving the accuracy of evolutionarily stable strategies (ESS) calculations. The new technique addresses limitations in existing models by incorporating decision-making errors, ensuring reliable convergence for dynamic game theory.

Area of Science:

  • Evolutionary Game Theory
  • Animal Behavior
  • Computational Biology

Background:

  • Modeling animal contests often involves complex, state-dependent decisions.
  • Traditional methods for calculating evolutionarily stable strategies (ESS) using best response maps can suffer from discontinuities, leading to convergence issues and uncertain equilibrium identification.
  • Existing computational techniques may not reliably determine Nash equilibria in dynamic games.

Purpose of the Study:

  • To present a novel computational technique for analyzing state-dependent dynamic games in animal contests.
  • To overcome the limitations of traditional iteration methods by incorporating decision-making errors.
  • To provide a robust method for computing evolutionarily stable strategies (ESS) and Nash equilibria.

Main Methods:

Related Experiment Videos

  • Development of a general computational technique based on incorporating errors in decision-making processes.
  • Application and validation of the technique using the Hawk-Dove game with a known analytical solution.
  • General theoretical analysis of the technique's convergence properties for complex games.

Main Results:

  • The proposed computational technique effectively resolves convergence issues associated with discontinuous best response maps.
  • The method successfully computes ESS in the Hawk-Dove game, aligning with known analytical solutions.
  • The technique demonstrates general applicability and reliability for more complex game scenarios.

Conclusions:

  • The new computational approach offers a reliable method for determining evolutionarily stable strategies (ESS) in state-dependent animal contests.
  • Incorporating decision-making errors provides a biologically justifiable and computationally advantageous solution to complex game theory problems.
  • This method enhances the accuracy and feasibility of modeling dynamic strategic interactions in evolutionary biology.