Integrated Information Increases with Fitness in the Evolution of Animats
Abstract
One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.
Additional Information
© 2011 Edlund et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received March 8, 2011; Accepted September 3, 2011; Published October 20, 2011. Editor: Lyle J. Graham, Université Paris Descartes, Centre National de la Recherche Scientifique, France. Funding: This work was funded in part by the Paul G. Allen Family Foundation, by the National Science Foundation's Frontiers in Integrative Biological Research grant FIBR-0527023, NSF's BEACON Center for the Study of Evolution in Action under contract No. DBI-0939454, and by the WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-10008). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We would like to thank David Balduzzi, Virgil Griffith, Nikhil J. Joshi, Sang Wan Lee, and Jory Schossau, and acknowledge detailed and insightful reviewer comments. Author Contributions: Conceived and designed the experiments: JAE AH CK GT CA. Performed the experiments: JAE AH. Analyzed the data: JAE AH. Contributed reagents/materials/analysis tools: NC. Wrote the paper: JAE CK GT CA.Attached Files
Published - Edlund2011p16552Plos_Comput_Biol.pdf
Supplemental Material - FigureS1.pdf
Supplemental Material - TextS1.pdf
Supplemental Material - TextS2.pdf
Supplemental Material - TextS3.pdf
Supplemental Material - VideoS1.mp4
Supplemental Material - VideoS2.mp4
Supplemental Material - VideoS3.mp4
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Additional details
- PMCID
- PMC3197648
- Eprint ID
- 28588
- Resolver ID
- CaltechAUTHORS:20111223-104836001
- Paul G. Allen Family Foundation
- FIBR-0527023
- NSF
- DBI-0939454
- NSF
- R31-10008
- National Research Foundation of Korea
- Created
-
2012-01-09Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field
- Caltech groups
- Koch Laboratory (KLAB)