Abstract
We have identified what we think the GA is processing—building blocks; we have ensured that there is a sufficient initial supply of BBs and that the best ones grow in market share on average; and just now, we have taken the time to understand how long such market share growth takes, but how do we know whether the best building blocks are actually the ones that come to dominate the population? Answering this question is the focus of this chapter. Specifically, building on the identification of the building block decision problem as a problem in statistical decision making (Holland, 1973), we examine a number of little models of BB decision making. Starting with the generation-wise decision model that gave an initial bound on the relation between solution quality and population size, we conclude by presenting a simple, accurate model based on the solution to the gambler’s ruin problem. In the best tradition of little models, this back-of-an-envelope calculation is giving surprisingly accurate estimates of decision quality across a range of population sizes, problem sizes and complexity, and GA operators and selection schemes.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Goldberg, D.E. (2002). Deciding Well. In: The Design of Innovation. Genetic Algorithms and Evolutionary Computation, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3643-4_10
Download citation
DOI: https://doi.org/10.1007/978-1-4757-3643-4_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-3645-8
Online ISBN: 978-1-4757-3643-4
eBook Packages: Springer Book Archive