the Baldwin effect

Jay : game learning : ideas : Baldwin

In biology, the “Baldwin effect” is the result of the interaction of evolution with learning by individual animals over their lifetime. It turns out that individual learning can enhance evolutionary learning at the species level. The effect is named after J. Mark Baldwin, who described it in 1896.

In machine learning, the Baldwin effect means that you may be able to improve the results of an evolutionary algorithm by applying it to systems that themselves learn.

references

- A New Factor in Evolution (1896)
J. Mark Baldwin
The original paper.

- Evolution, Learning, and Instinct: 100 Years of the Baldwin Effect (1996)
Peter Turney, Darrell Whitley, Russell Anderson
A short piece with historical background. It points out that the full picture is much more complicated than “it’s a win if the individuals in your population learn.”

- The Baldwin Effect: A Bibliography
Reiji Suzuki (the current maintainer)
Web page. A fantastic resource on the Baldwin effect, largely but not exclusively from the point of view of machine learning.


updated 1 May 2012