1. What have the authors contributed in "Linmap: visualizing complexity gradients in evolutionary landscapes" ?
LinMap this paper is an interactive visualization tool for exploring the complexity gradients in evolutionary landscapes, which combines a rich variety of dynamic behaviors with a high level of computational efficiency.
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![Figure 8. (Color version in Supplementary Material.) An example of increasing the resolution in a chosen region (N = 12, K = 12, E = [0, 1.0], W = [0.1, 2.0]). First, a region of interest is identified and selected (left). The chosen region can then be enlarged and sampled at a higher resolution (center). It is also possible for regions of more than one resolution to be displayed in a single map: Upon zooming back out to the original map, the enlarged region is highlighted and displayed at the increased resolution (right).](/figures/figure-8-color-version-in-supplementary-material-an-example-2xqnkyqv.webp)
![Figure 9. (Color version in Supplementary Material.) Four complexity heat maps for the slice of parameter space (N = 8, K = 8, E = [0, 1.0], W = [0.01, 2.0]). The four complexity metrics are: number of terminal cells (top left), number of differentiated cells (top right), nondeterministic complexity (bottom left), and weighted complexity (bottom right).](/figures/figure-9-color-version-in-supplementary-material-four-2rfe1pkm.webp)
![Figure 7. (Color version in Supplementary Material.) Three instances of the same heat map at increasing levels of resolution (N = 12, K = 12, E = [0, 1.0], W = [0.1, 2.0]). The initial heat map (left) provides a rapid means of assessing whether this particular region of parameter space is interesting and worth exploring further. The resolution may then be interactively increased (center and right) by interpolating between existing parameter values.](/figures/figure-7-color-version-in-supplementary-material-three-hj1iyhgw.webp)