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

Evolutionary stability on graphs.

Hisashi Ohtsuki1, Martin A Nowak

  • 1Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA. ohtsuki@fas.harvard.edu

Journal of Theoretical Biology
|February 26, 2008
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

Large language models instantiate evolutionarily robust strategies of cooperation.

PNAS nexus·2026
Same author

Evolution of dispersal in a spatially heterogeneous population with finite patch sizes and catastrophes.

Journal of theoretical biology·2026
Same author

Age distinguishes selection from causation in cancer genomes.

Nature genetics·2026
Same author

Reply to Sacco: Complete spaces as outcomes of evolutionary optimization.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Payoff equivalence and complete strategy spaces of direct reciprocity.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Revealing the Drivers Underlying Distinct Evolutionary Trajectories in Lung Adenocarcinoma.

bioRxiv : the preprint server for 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
Same journal

Misspecification of the generation time distribution and its impact on R<sub>t</sub> estimates in structured populations.

Journal of theoretical biology·2026
Same journal

Stability-driven assembly meets Prigoginian informational dissipation. A mean-field ODE comment of entropy reduction and emergent proto-self.

Journal of theoretical biology·2026
See all related articles

This study explores evolutionary stability in games played on graphs. We found that population structure significantly impacts evolutionary stable strategies (ESS), with conditions differing from well-mixed populations.

Area of Science:

  • Evolutionary Game Theory
  • Mathematical Biology
  • Network Science

Background:

  • Evolutionary stability is crucial in game theory, defining strategies that resist invasion in a population.
  • Population structure, such as networks, can alter evolutionary dynamics.
  • Previous research highlights the impact of structure on evolutionary outcomes.

Purpose of the Study:

  • To derive and analyze the conditions for evolutionary stability on graphs.
  • To investigate how different population structures and update rules affect evolutionary stable strategies (ESS).
  • To compare theoretical predictions with simulation results for games on graphs.

Main Methods:

  • Derivation of analytical conditions for evolutionary stability on regular graphs (degree k > 2).

Related Experiment Videos

  • Computer simulations on random regular graphs and lattices.
  • Analysis of three update rules: birth-death (BD), death-birth (DB), and imitation (IM).

    • Main Results:

    • Evolutionary stability on sparse graphs is not equivalent to stability in well-mixed populations.
    • Analytical conditions for ESS were derived for regular graphs.
    • Simulation results validated theoretical predictions for various graph structures and update rules.

    Conclusions:

    • Population structure fundamentally influences evolutionary stability in game theory.
    • The conditions for evolutionary stable strategies (ESS) are context-dependent on the underlying graph structure.
    • A geometrical interpretation of ESS conditions on graphs was provided.