Long-term evolutionary dynamics in heterogeneous cellular automata

David Medernach, Taras Kowaliw, Conor Ryan, René Doursat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work we study open-ended evolution through the analysis of a new model, HetCA, for "heterogeneous cellular automata". Striving for simplicity, HetCA is based on classical two-dimensional CA, but differs from them in several key ways: cells include properties of "age", "decay", and "quiescence"; cells utilize a heterogeneous transition function, one inspired by genetic programming; and there exists a notion of genetic transfer between adjacent cells. The cumulative effect of these changes is the creation of an evolving ecosystem of competing cell colonies. To evaluate the results of our new model, we define a measure of phenotypic diversity on the space of cellular automata. Via this measure, we contrast HetCA to several controls known for their emergent behaviours- homogeneous CA and the Game of Life-and several variants of our model. This analysis demonstrates that HetCA has a capacity for long-term phenotypic dynamics not readily achieved in other models. Runs exceeding one million time steps do not exhibit stagnation or even cyclic behaviour. Further, we show that the design choices are well motivated, as the exclusion of any one of them disrupts the long-term dynamics.

Original languageEnglish
Title of host publicationGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference
Pages231-238
Number of pages8
DOIs
Publication statusPublished - 2013
Event2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013 - Amsterdam, Netherlands
Duration: 6 Jul 201310 Jul 2013

Publication series

NameGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference

Conference

Conference2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013
Country/TerritoryNetherlands
CityAmsterdam
Period6/07/1310/07/13

Keywords

  • Artificial ecosystem
  • Cellular automata
  • Evolution
  • Genetic programming
  • Open-ended

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