Hyperspace geography: Visualizing fitness landscapes beyond 4D

Wiles, J. and Tonkes, B. (2006) Hyperspace geography: Visualizing fitness landscapes beyond 4D. Artificial Life, 12 2: 211-216. doi:10.1162/106454606776073387

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Author Wiles, J.
Tonkes, B.
Title Hyperspace geography: Visualizing fitness landscapes beyond 4D
Journal name Artificial Life   Check publisher's open access policy
ISSN 1064-5462
Publication date 2006
Sub-type Article (original research)
DOI 10.1162/106454606776073387
Open Access Status File (Publisher version)
Volume 12
Issue 2
Start page 211
End page 216
Total pages 6
Editor M. A. Bedau
Place of publication Cambridge, Massachusetts, U.S.A.
Publisher M I T Press
Collection year 2006
Language eng
Abstract Human perception is finely tuned to extract structure about the 4D world of time and space as well as properties such as color and texture. Developing intuitions about spatial structure beyond 4D requires exploiting other perceptual and cognitive abilities. One of the most natural ways to explore complex spaces is for a user to actively navigate through them, using local explorations and global summaries to develop intuitions about structure, and then testing the developing ideas by further exploration. This article provides a brief overview of a technique for visualizing surfaces defined over moderate-dimensional binary spaces, by recursively unfolding them onto a 2D hypergraph. We briefly summarize the uses of a freely available Web-based visualization tool, Hyperspace Graph Paper (HSGP), for exploring fitness landscapes and search algorithms in evolutionary computation. HSGP provides a way for a user to actively explore a landscape, from simple tasks such as mapping the neighborhood structure of different points, to seeing global properties such as the size and distribution of basins of attraction or how different search algorithms interact with landscape structure. It has been most useful for exploring recursive and repetitive landscapes, and its strength is that it allows intuitions to be developed through active navigation by the user, and exploits the visual system's ability to detect pattern and texture. The technique is most effective when applied to continuous functions over Boolean variables using 4 to 16 dimensions.
Keyword Hyperspace graph paper
Fitness landscapes
Cost surfaces
Royal road
Hierarchical If-and-only-if
Q-Index Code C1

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Created: Wed, 15 Aug 2007, 08:23:18 EST