Escalation of Memory Length in Finite Populations

Escalation of Memory Length in Finite Populations The escalation of complexity is a commonly cited benefit of coevolutionarysystems, but computational simulations generally fail to demonstrate thiscapacity to a satisfactory degree. We draw on a macroevolutionary theory ofescalation to develop a set of criteria for coevolutionary systems to exhibitescalation of strategic complexity. By expanding on a previously developed modelof the evolution of memory length for cooperative strategies by KristianLindgren, we resolve previously observed limitations on the escalation of memorylength by extending operators of evolutionary variation. We present long-termcoevolutionary simulations showing that larger population sizes tend to supportgreater escalation of complexity than smaller ones do. Additionally, weinvestigate the sensitivity of escalation during transitions of complexity. TheLindgren model has often been used to argue that the escalation of competitivecoevolution has intrinsic limitations. Our simulations show that coevolutionaryarms races can continue to escalate in computational simulations givensufficient population sizes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Life MIT Press

Escalation of Memory Length in Finite Populations

Artificial Life, Volume 25 (1): 11 – Apr 1, 2019

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Publisher
MIT Press
Copyright
Copyright © MIT Press
ISSN
1064-5462
eISSN
1530-9185
D.O.I.
10.1162/artl_a_00278
Publisher site
See Article on Publisher Site

Abstract

The escalation of complexity is a commonly cited benefit of coevolutionarysystems, but computational simulations generally fail to demonstrate thiscapacity to a satisfactory degree. We draw on a macroevolutionary theory ofescalation to develop a set of criteria for coevolutionary systems to exhibitescalation of strategic complexity. By expanding on a previously developed modelof the evolution of memory length for cooperative strategies by KristianLindgren, we resolve previously observed limitations on the escalation of memorylength by extending operators of evolutionary variation. We present long-termcoevolutionary simulations showing that larger population sizes tend to supportgreater escalation of complexity than smaller ones do. Additionally, weinvestigate the sensitivity of escalation during transitions of complexity. TheLindgren model has often been used to argue that the escalation of competitivecoevolution has intrinsic limitations. Our simulations show that coevolutionaryarms races can continue to escalate in computational simulations givensufficient population sizes.

Journal

Artificial LifeMIT Press

Published: Apr 1, 2019

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