HTML Export for Dagstuhl Seminar Proceedings, Volume 8051

Copy to Clipboard Download

<h2>Dagstuhl Seminar Proceedings, Volume 8051, </h2>
<ul>
<li>
    <span class="authors">Dirk V. Arnold, Anne Auger, Carsten Witt, and Jonathan E. Rowe</span>
    <span class="title">08051 Abstracts Collection – Theory of Evolutionary Algorithms</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.1">10.4230/DagSemProc.08051.1</a>
</li>
<li>
    <span class="authors">Dirk V. Arnold, Anne Auger, Jonathan E. Rowe, and Carsten Witt</span>
    <span class="title">08051 Executive Summary – Theory of Evolutionary Algorithms</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.2">10.4230/DagSemProc.08051.2</a>
</li>
<li>
    <span class="authors">Jun He, Yuren Zhou, and Xin Yao</span>
    <span class="title">A Comparison of GAs Penalizing Infeasible Solutions and Repairing Infeasible Solutions on the 0-1 Knapsack Problem</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.3">10.4230/DagSemProc.08051.3</a>
</li>
<li>
    <span class="authors">Boris S. Mitavskiy and Chris Cannings</span>
    <span class="title">Evaluating Stationary Distribution of the Binary GA Markov Chain in Special Cases</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.4">10.4230/DagSemProc.08051.4</a>
</li>
<li>
    <span class="authors">Nicholas Freitag McPhee and Riccardo Poli</span>
    <span class="title">N-gram GP: Early results and half-baked ideas</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.5">10.4230/DagSemProc.08051.5</a>
</li>
<li>
    <span class="authors">Dirk Sudholt and Carsten Witt</span>
    <span class="title">Runtime Analysis of Binary PSO</span>
    <a class="doi" href="https://doi.org/10.4230/DagSemProc.08051.6">10.4230/DagSemProc.08051.6</a>
</li>
</ul>

The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.

Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode