Graph product representation of organism-environment couplings in evolution

Research output: Contribution to conferencePaper

Abstract

We present a theoretical framework that mathematically formulates the evolutionary dynamics of organism-environment couplings using graph product multilayer networks, i.e., networks obtained by “multiplying” factor networks using some graph product operator. In this framework, one factor network represents different options of environments and their mutual physical reachability, and another factor network represents possible types of organisms and their mutual evolutionary reachability. The organism-environment coupling space is given by a Cartesian product of these two factor networks, and the nodes of the product network represent specific organism-environment combinations. We studied a simple evolutionary model using a reaction-diffusion equation on this organism-environment coupling space. We numerically calculated correlations between the inherent fitness of organisms and the actual average fitness obtained from the graph product-based evolutionary model, varying the spatial diffusion rate while keeping the type diffusion rate small. Results demonstrated that, when the spatial diffusion is sufficiently slow, the correlation between inherent and actual fitnesses drops significantly, where it is no longer valid to assume that fitness can be attributed only to organisms.

Original languageEnglish
Pages412-413
Number of pages2
Publication statusPublished - 2020
Event2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019 - Newcastle upon Tyne, United Kingdom
Duration: 2019 Jul 292019 Aug 2

Conference

Conference2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019
CountryUnited Kingdom
CityNewcastle upon Tyne
Period19/7/2919/8/2

ASJC Scopus subject areas

  • Modelling and Simulation

Fingerprint Dive into the research topics of 'Graph product representation of organism-environment couplings in evolution'. Together they form a unique fingerprint.

  • Cite this

    Sayama, H. (2020). Graph product representation of organism-environment couplings in evolution. 412-413. Paper presented at 2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019, Newcastle upon Tyne, United Kingdom.