| Evolution of a multi-agent system in a cyclical environment. | |
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MedLine Citation:
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PMID: 18414915 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The synchronisation phenomena in biological systems is a current and recurring subject of scientific study. This topic, namely that of circadian clocks, served as inspiration to develop an agent-based simulation that serves the main purpose of being a proof-of-concept of the model used in the BitBang framework, that implements a modern autonomous agent model. Despite having been extensively studied, circadian clocks still have much to be investigated. Rather than wanting to learn more about the internals of this biological process, we look to study the emergence of this kind of adaptation to a daily cycle. To that end we implemented a world with a day/night cycle, and analyse the ways the agents adapt to that cycle. The results show the evolution of the agents' ability to gather food. If we look at the total number of agents over the course of an experiment, we can pinpoint the time when reproductive technology emerges. We also show that the agents adapt to the daily cycle. This circadian rhythm can be shown by analysing the variation on the agents metabolic rate, which is affected by the variation of their movement patterns. In the experiments conducted we can observe that the metabolic rate of the agents varies according to the daily cycle. |
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Authors:
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Tiago Baptista; Ernesto Costa |
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Publication Detail:
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Type: Journal Article Date: 2008-04-15 |
Journal Detail:
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Title: Theory in biosciences = Theorie in den Biowissenschaften Volume: 127 ISSN: 1611-7530 ISO Abbreviation: Theory Biosci. Publication Date: 2008 Jun |
Date Detail:
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Created Date: 2008-05-15 Completed Date: 2008-06-18 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9708216 Medline TA: Theory Biosci Country: Germany |
Other Details:
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Languages: eng Pagination: 141-8 Citation Subset: IM |
Affiliation:
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CISUC, Department of Informatics Engineering, University of Coimbra, Polo II, Pinhal de Marrocos, 3030-290, Coimbra, Portugal. baptista@dei.uc.pt |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Animals Artificial Intelligence* Biological Clocks / physiology* Biomimetics / methods* Circadian Rhythm / physiology* Evolution* Feeding Behavior / physiology* Humans Models, Biological* Population Dynamics |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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