Illuminating meaningful diversity in complex feature spaces through adaptive grid-based genetic algorithms

In many fields there exist problems for which multiple solutions of suitably high performance may be found across distinct regions of the search space. Optimisation of the search towards including these distinct solutions is important not only to understanding these spaces but also to avoiding local optima. This is the goal of a type of genetic algorithms called illumination algorithms. In Chapter 2, we demonstrate the use of an illumination algorithm in the exploration of networks sharing only a given set of structural features (valid networks). This method produces a population of valid networks that are more diverse than those produced using state of the art methods, however, it was found to be too inefficient to be usable in real-world problems. Additionally, setting an appropriate resolution of the search requires some amount of prior knowledge of the space of solutions. Addressing this problem is the focus of Chapter 3, in which we develop three extensions to the method: a) an exact method of mutation whereby only valid networks are explored, b) an adaptive mechanism for setting the resolution of the search, c) a principle for tuning mutations parameters to the search’ s resolution. We show that with these additions our method is able to increase the diversity of solutions found in significantly fewer iterations. Finally, in Chapter 4 we expand our method for use in more general problem spaces. We benchmark it against the state of the art. In all tested landscapes, we show that our method is able to identify more meaningful niches in the spaces in the same number of iterations. We conclude by highlighting the limits of our framework and discuss further directions

Using novelty-biased GA to sample diversity in graphs satisfying constraints

The structure of the network underlying many complex systems, whether artificial or natural, plays a significant role in how these systems operate. As a result, much emphasis has been placed on accurately describing networks using network theoretic metrics. When it comes to generating networks with similar properties, however, the set of available techniques and properties that can be controlled for remains limited. Further, whilst it is becoming clear that some of the metrics currently used to control the generation of such networks are not very prescriptive so that networks could potentially exhibit very different higher-order structure within those constraints, network generating algorithms typically produce fairly contrived networks and lack mechanisms by which to systematically explore the space of network solutions. In this paper, we explore the potential of a multi-objective novelty-biased GA to provide a viable alternative to these algorithms. We believe our results provide the first proof of principle that (i) it is possible to use GAs to generate graphs satisfying set levels of key classical graph theoretic properties and (ii) it is possible to generate diverse solutions within these constraints. The paper is only a preliminary step, however, and we identify key avenues for further development

A comparative study of the efficiency of chart versus computer-generated contrast sensitivity testing in glaucoma patients and controls

Purpose. The goal of this study was to assess the efficiency of chart vs. computergenerated contrast sensitivity tests in glaucoma patients and controls. Methods. A total of 64 individuals (30 young controls, 18 older controls, 16 glaucoma patients) were tested for contrast sensitivity using 4 different tests. Two tests determined contrast sensitivity (CS) for detecting large targets with sharp borders. One of these was the MARS printed chart, and the other a computerized number search test by Bailey. The second assessment determined spatial contrast sensitivity (SCS) for sinusoidal grating targets at several spatial frequencies. One of these was the printed Vistech chart, the other a computerized test by Faubert. Results. Both CS tests showed a decrease in the glaucoma group versus both the control groups (p < 0.001). The tests for SCS demonstrated a decrease in sensitivity both with age (p < 0.001) and in the presence of glaucoma (p < 0.001) across all spatial frequencies. Conclusion. The data indicated that SCS was superior in separating the three study groups. Neither of the computer-generated tests was more sensitive than its printed counterpart

Multilayer distortion in the reconstructed (110) surface of Au

A new LEED intensity analysis of the reconstructed Au(110)-(1×2) surface results in a modification of the missing row model with considerable distortions which are at least three layers deep. The top layer spacing is contracted by about 20%, the second layer exhibits a lateral pairing displacement of 0.07 Å and the third layer is buckled by 0.24 Å. Distortions in deeper layers seem to be probable but have not been considered in this analysis. The inter-atomic distances in the distorted surface region show both an expansion and a contraction compared to the bulk value and range from 5% contraction to about 4% expansion

Laser desorption from and reconstruction on Si(100) surfaces studied by scanning tunneling microscopy

Laser irradiated Si(100) surfaces were studied with an ultrahigh-vacuum scanning tunneling microscopy (STM) system. Our observations indicate that only the dimerized outermost atomic layer is removed if the laser fluence is below the melting threshold with a photon energy larger than the band gap. The newly exposed layer, surprisingly, did not have a dimerized atomic structure, but rather, resembled that of a bulk-terminated structure. The uncovered layer remained atomically smooth (no vacancies) even after 90% of the outermost layer was removed. A possible explanation of these observations is that atom removal occurs by a preferential breakage of the atomic bonds in defect sites. When the laser fluence was increased to levels above the melting threshold, extensive surface roughening occurs