research-article

On the evolution of motility and intelligent tactic response

Authors:

Laura M. Grabowski,

Wesley R. Elsberry,

Robert T. PennockAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 209 - 216

https://doi.org/10.1145/1389095.1389129

Published: 12 July 2008 Publication History

Abstract

We present our first results concerning the de novo evolution of motility and tactic response in systems of digital organisms. Our model organism was E. coli and the behavior of interest was gradient following, since this represents simple decision-making. Our first experiments demonstrated the evolution of a tactic response, both when provided with a hand-coded system to remember previous gradient concentrations and without this crutch where the organisms must determine how to store previous values on their own. In our second set of experiments we investigated two different rotation strategies, random and systematic, and found no significant performance difference between the two strategies. These experiments served as a stepping-stone and proof-of-concept of the infrastructure needed for our future work on the evolution of simple intelligence.

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Cited By

Bryson DWagner AOfria CArnold D(2014)There and back againProceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation10.1145/2576768.2598363(689-696)Online publication date: 12-Jul-2014
https://dl.acm.org/doi/10.1145/2576768.2598363
Bryson DOfria C(2013)Understanding Evolutionary Potential in Virtual CPU Instruction Set ArchitecturesPLoS ONE10.1371/journal.pone.00832428:12(e83242)Online publication date: 23-Dec-2013
https://doi.org/10.1371/journal.pone.0083242
Pietruszkiewicz WImada A(2013)Artificial Intelligence Evolved from Random Behaviour: Departure from the State of the ArtArtificial Intelligence, Evolutionary Computing and Metaheuristics10.1007/978-3-642-29694-9_2(19-41)Online publication date: 2013
https://doi.org/10.1007/978-3-642-29694-9_2
Show More Cited By

Index Terms

On the evolution of motility and intelligent tactic response
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
  2. Modeling and simulation

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Bryson DWagner AOfria CArnold D(2014)There and back againProceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation10.1145/2576768.2598363(689-696)Online publication date: 12-Jul-2014
https://dl.acm.org/doi/10.1145/2576768.2598363
Bryson DOfria C(2013)Understanding Evolutionary Potential in Virtual CPU Instruction Set ArchitecturesPLoS ONE10.1371/journal.pone.00832428:12(e83242)Online publication date: 23-Dec-2013
https://doi.org/10.1371/journal.pone.0083242
Pietruszkiewicz WImada A(2013)Artificial Intelligence Evolved from Random Behaviour: Departure from the State of the ArtArtificial Intelligence, Evolutionary Computing and Metaheuristics10.1007/978-3-642-29694-9_2(19-41)Online publication date: 2013
https://doi.org/10.1007/978-3-642-29694-9_2
Connelly BMcKinley PBeckmann B(2009)Evolving cooperative pheromone usage in digital organisms2009 IEEE Symposium on Artificial Life10.1109/ALIFE.2009.4937711(184-191)Online publication date: Mar-2009
https://doi.org/10.1109/ALIFE.2009.4937711
Elsberry WGrabowski LOfria CPennock R(2009)Cockroaches, drunkards, and climbers: Modeling the evolution of simple movement strategies using digital organisms2009 IEEE Symposium on Artificial Life10.1109/ALIFE.2009.4937699(92-99)Online publication date: Mar-2009
https://doi.org/10.1109/ALIFE.2009.4937699

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