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The effect of complexity on the opti...

Bravo, Rafael Bravo.

The effect of complexity on the optimal rate of trait mutation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The effect of complexity on the optimal rate of trait mutation.
Author:	Bravo, Rafael Bravo.
Published:	Ann Arbor : ProQuest Dissertations & Theses, 2017
Description:	55 p.
Notes:	Source: Masters Abstracts International, Volume: 56-03.
Notes:	Adviser: Jefferey Schank.
Contained By:	Masters Abstracts International56-03(E).
Subject:	Computer science.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10193357
ISBN:	9781369615111

The effect of complexity on the optimal rate of trait mutation.
Bravo, Rafael Bravo.

The effect of complexity on the optimal rate of trait mutation. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 55 p.

Source: Masters Abstracts International, Volume: 56-03.

Thesis (M.S.)--University of California, Davis, 2017.

This project explores how complexity affects the optimal rates of mutation in an evolving ecosystem. To examine this, I created a 2D model of multicellular life in which natural selection acted on agents or "bodies" whose traits were mutated directly. Different versions of the model involved different levels of body complexity: The 1st level consisted of single cells with fixed abilities and evolving neural networks; the 2nd level added evolvable abilities; the 3rd added evolvable multicellular bodies; the 4th added evolvable communication between cells within the same body. A number of tests confirmed the essential properties of the model: Ecosystems at later time-points were pitted against those from earlier time-points, and their superiority confirmed that non-local adaptation was occurring for each level. Ecosystems from higher complexity levels were pitted against those from lower levels, and their superiority confirmed that added evolutionary flexibility increased fitness Overall, the results of these tests indicated that the model is an appropriate substrate for examining how complexity affects the optimal rate of evolution. I then found, for each level, the mutation rate parameters that produced the highest fitness. One parameter, the mutation rate of the weight matrix, was common to all levels. The optimal mutation rate for this parameter tended to increase with increasing model complexity, possibly because the larger evolutionary space created by increased complexity favors a faster search.

ISBN: 9781369615111Subjects--Topical Terms:

199325
Computer science.

The effect of complexity on the optimal rate of trait mutation.
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520 $a This project explores how complexity affects the optimal rates of mutation in an evolving ecosystem. To examine this, I created a 2D model of multicellular life in which natural selection acted on agents or "bodies" whose traits were mutated directly. Different versions of the model involved different levels of body complexity: The 1st level consisted of single cells with fixed abilities and evolving neural networks; the 2nd level added evolvable abilities; the 3rd added evolvable multicellular bodies; the 4th added evolvable communication between cells within the same body. A number of tests confirmed the essential properties of the model: Ecosystems at later time-points were pitted against those from earlier time-points, and their superiority confirmed that non-local adaptation was occurring for each level. Ecosystems from higher complexity levels were pitted against those from lower levels, and their superiority confirmed that added evolutionary flexibility increased fitness Overall, the results of these tests indicated that the model is an appropriate substrate for examining how complexity affects the optimal rate of evolution. I then found, for each level, the mutation rate parameters that produced the highest fitness. One parameter, the mutation rate of the weight matrix, was common to all levels. The optimal mutation rate for this parameter tended to increase with increasing model complexity, possibly because the larger evolutionary space created by increased complexity favors a faster search.
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