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Implementing phenotypic plasticity with an adaptive generative representation

conference contribution
posted on 2023-05-23, 14:14 authored by Ashlock, D, Ashlock, W, Erin MontgomeryErin Montgomery
This study compares an adaptive and a nonadaptive representation for finding long walks on obstructed grids. This process models adaption of a simple plant to an environment where the plant's ability to grow is impeded by obstructions such as resource poor areas like bare rock. The intent of the adaptive representation is to model the biological phenomenon of phenotypic plasticity in which gene regulation is at least partially in response to environmental cues, in this case the obstructions. The adaptive representation is found to have a substantial advantage, with the greatest level of advantage at intermediate levels of obstruction. Agents are asked to solve multiple problem instances simultaneously (i.e. using the same chromosome). The advantage of the adaptive representation is also found to be higher when more boards are used in fitness evaluation.

History

Publication title

Proceedings of the 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Pagination

173-180

ISBN

978-1-7281-1462-0

Department/School

School of Information and Communication Technology

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

United States

Event title

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Event Venue

Siena, Italy

Date of Event (Start Date)

2019-07-09

Date of Event (End Date)

2019-07-11

Rights statement

Copyright 2019 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the information and computing sciences

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