Evolutionary models for maternal effects in simulated developmental systems

ABSTRACT

Maternal influence on offspring goes beyond strict nuclear (DNA) inheritance: inherited maternal mRNA, mitochondria, caring and nurturing are all additional sources that affect offspring development, and they can be also shaped by evolution. These additional factors are called maternal effects, and their important role in evolution is well established experimentally. This paper presents two models for maternal effects, based on a genetic algorithm and simulated development of neural networks. We extended a model by Eggenberger by adding two mechanisms for maternal effects: the first mechanism attempts to replicate maternal cytoplasmic control, while the second mechanism replicates interactions between the fetus and the uterine environment. For examining the role of maternal effects in artificial evolution, we evolved networks for the odd-3-parity problem, using increasing rates of maternal influence. Experiments have shown that maternal effects increase adaptiveness in the latter model.

REFERENCES

• 1: Peter Eggenberger Hotz , Gabriel Gómex , Rolf Pfeifer, Evolving the morphology of a neural network for controlling a foveating retina: and its test on a real robot, Proceedings of the eighth international conference on Artificial life, p.243-251, December 09-13, 2002
• 2: F. Gruau. Neural Network Synthesis using Cellular Encoding and the Genetic Algorithm. PhD thesis, Laboratoire de la Informatique du Parallelisme, Ecole Normale Superieure de Lyon, 1994.
• 3: M. Rossiter. Incidence and consequences of inherited environmental effects. Annual Review of Ecology and Systematics, 27:451--476, November 1996.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Connectionism and neural nets

General Terms:
Algorithms

Keywords:
artificial embriogeny, genetic algorithms, maternal effects, neural networks