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Simplicity and complexity in MIRROR universes.

P Hogeweg1

  • 1Bioinformatica, Utrecht, The Netherlands.

Bio Systems
|January 1, 1989
PubMed
Summary
This summary is machine-generated.

Biological systems exhibit complexity arising from simple individual actions. The MIRROR methodology reconciles simplicity with biological complexity, offering insights into the evolution of life.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Evolutionary Biology

Background:

  • Classical modeling tools enforce simplicity, shaping the concept of scientific simplicity (Occam's razor).
  • Biological systems are characterized by inherent complexity, posing challenges for traditional modeling approaches.
  • Computer models offer greater flexibility regarding simplicity constraints compared to other modeling paradigms.

Purpose of the Study:

  • To introduce and discuss the MIRROR modeling methodology.
  • To reconcile the principle of simplicity with the inherent complexity of biological systems.
  • To propose an unconventional view of the evolution of complexity in biotic systems.

Main Methods:

  • The MIRROR methodology defines simplicity through the "TODO" (do what there is to do) actions of individual components (molecules, cells, organisms).

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  • Complexity emerges from the interactions of multiple levels of individuals and observable behaviors within the model universe.
  • Case studies illustrate the development of complex, self-regulating social structures from simple individual interactions.

    • Main Results:

    • Demonstrated how simple individual interactions can lead to the emergence of complex, self-regulating systems.
    • Compared the adaptability of "TODO"-based entities with that of evolving entities.
    • Presented examples suggesting a novel perspective on the evolution of biotic complexity.

    Conclusions:

    • The MIRROR methodology provides a framework for studying biological complexity by grounding it in simple individual behaviors.
    • Observed patterns in the molecular record of biotic evolution appear consistent with the proposed model of complexity evolution.
    • This approach offers new avenues for understanding the intricate nature of life's development and adaptation.