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Process Information and Evolution.

Erick Chastain1, Cameron Smith2

  • 1Department of Computer Science, Rutgers University, New Brunswick, NJ, 08901 USA.

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
|August 16, 2017
PubMed
Summary
This summary is machine-generated.

Universal Semantic Communication (USC) theory connects agents without fixed protocols to evolutionary processes. Evolving populations use process information to semantically interpret their environments, mirroring problem-solving in USC.

Keywords:
AlgorithmsBiological information theoryEvolution (biology)GeneticsInformation theoryLearning systemsSemantics

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Area of Science:

  • Information Theory
  • Evolutionary Biology
  • Computational Neuroscience

Background:

  • Universal Semantic Communication (USC) models agent communication without predefined protocols.
  • Evolutionary processes involve adaptation and information processing within populations.
  • Understanding semantic aspects of evolution is crucial for biological and artificial systems.

Purpose of the Study:

  • To demonstrate a connection between a special case of USC and evolutionary processes.
  • To introduce the concept of 'process information' as a bridge between USC and evolution.
  • To explore the semantic information internalized by evolving populations.

Main Methods:

  • Modeling environmental signals as originating from alternative agents.
  • Correlating intrinsic information with environmental input for signal interpretation.
  • Applying the concept of 'process information' to analyze evolutionary dynamics.

Main Results:

  • Evolution is shown to be a method for solving specific USC problems.
  • Evolutionary processes can be viewed as a special case of the Multiplicative Weights Updates algorithm.
  • Infinite population selection without mutation or recombination aligns with the Rivoire-Leibler model.

Conclusions:

  • Evolving populations implicitly acquire semantic information about their environments.
  • Process information provides a framework for understanding semantic interpretation in evolving systems.
  • USC offers insights into the semantic underpinnings of evolutionary mechanisms.