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A model of evolution and learning.

Vladimir G Red'ko1, Oleg P Mosalov, Danil V Prokhorov

  • 1Institute of Optical Neural Technologies, Russian Academy of Science, Vavilova Str., 44/2, Moscow 119333, Russian Federation. redko@iont.ru

Neural Networks : the Official Journal of the International Neural Network Society
|August 23, 2005
PubMed
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In evolving agent populations, learned behaviors can become genetically inherited through the Baldwin effect. This study models self-learning agents predicting stock prices, showing how adaptation influences evolution.

Area of Science:

  • Artificial Intelligence
  • Evolutionary Computation
  • Computational Finance

Background:

  • Agent-based modeling is crucial for understanding complex adaptive systems.
  • The interplay between individual learning and population-level evolution is a key area of research.
  • Artificial agents with adaptive learning mechanisms can model real-world economic behaviors.

Purpose of the Study:

  • To investigate the interaction between learning and evolution in a population of self-learning agents.
  • To analyze how acquired adaptive behaviors are inherited through evolution.
  • To model agent-brokers predicting stock price changes and their adaptive strategies.

Main Methods:

  • Developed a computational model of evolving populations of self-learning agents.

Related Experiment Videos

  • Implemented a neural network adaptive critic design for agent behavioral adaptation.
  • Simulated scenarios with active evolution, active learning, or both.
  • Observed and analyzed the Baldwin effect in agent behavior inheritance.

    • Main Results:

    • Demonstrated the occurrence of the Baldwin effect, where learned adaptive policies become inherited.
    • Showcased how initially acquired behavioral adaptations are integrated into the evolutionary process.
    • Identified parallels between agent-broker adaptive tactics and animal foraging behaviors.

    Conclusions:

    • Learning and evolution can synergistically drive adaptation in artificial populations.
    • The Baldwin effect provides a mechanism for rapid adaptation by integrating learned traits into the genetic framework.
    • Agent-based models offer valuable insights into evolutionary dynamics and adaptive strategies.