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Cited by 33Evolution and Genetic DynamicsComplex Systems and DynamicsPhilosophy and History of Science

Information theory, predictability and the emergence of complex life

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Seoane, Luís F., Solé, Ricard V.·2018·Royal Society Open Science
DOI 10.1098/rsos.172221PMC PMC5830796
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Abstract

Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the inevitable cost associated with detecting environmental cues and responding to them in adaptive ways, we conjecture that the potential for predicting the environment can overcome the expenses associated with maintaining costly, complex structures. We present a minimal formal model grounded in information theory and selection, in which successive generations of agents are mapped into transmitters and receivers of a coded message. Our agents are guessing machines and their capacity to deal with environments of different complexity defines the conditions to sustain more complex agents.

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    “In other words, living systems evolved mechanisms that could reduce the uncertainty of the environment [239–241].”

    From Fundamental constraints to the logic of living systems (2024) · cites this paper as [241]

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Cited by

Sorted by citations

Authors
Seoane, L. F., & Solé, R. V.
Affiliations
Institució Catalana de Recerca i Estudis Avançats (ES)
Corresponding author
Seoane, Luís F.
ORCID
Venue
Royal Society Open Science
Publisher
The Royal Society
Published
2018-02
Volume
5
Issue
2
Pages
172221
ISSN
2054-5703 (ISSN-L)
DOI
10.1098/rsos.172221
PMC
PMC5830796
OpenAlex
W2572219153
Cited by
33
References
5
Citations by year
2026: 1 · 2025: 3 · 2024: 2 · 2023: 1 · 2022: 4 · 2021: 5 · 2020: 5 · 2019: 8 · 2018: 4
FWCI
3.37
Type
journal article
Language
en
Open access
Licence
Locations
  • Royal Society Open Science (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
Funders
H2020 European Research Council (ERC SYNCOM 294294)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
Keywords
environmental predictability, information theory, environmental uncertainty, adaptive complexity, selection, agent-based modeling, coded messages, environmental complexity

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