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<!doctype html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no">
<title>Overview of Evolutionary Computation</title>
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<body>
<div class="reveal">
<div class="slides">
<section>
<h1>Evolutionary Computation</h1>
<h3>Overview</h3>
<br />
<img src="../imgs/logo.png" width="30%" height="auto">
</section>
<section>
<h2>Evolution</h2>
<h3>The Algorithm of Life</h3>
<br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/PGquZTg5qXs?start=18&autoplay=1&loop=1&controls=0&mute=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/lbHjs9A7sis?start=65&autoplay=1&loop=1&controls=0&mute=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/UQKC5pZ0FG8?autoplay=1&loop=1&controls=0&mute=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/7qfoFcBLsCI?autoplay=1&loop=1&controls=0&mute=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</section>
<section>
<h2>Evolutionary Algorithm</h2>
<br />
<img src="../imgs/AlgoG.png" width="30%" height="auto">
<br />
<br />
Same pattern for (almost) all evolutionary methods
</section>
<section>
<h2>Artifical Evolution in Action</h2>
<br />
<iframe width="560" height="315" src="https://www.youtube.com/embed/v9ofyPwzkxA?start=7&autoplay=1&mute=1&loop=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/z9ptOeByLA4?start=27&autoplay=1&mute=1&loop=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/qv6UVOQ0F44?start=285&autoplay=1&mute=1&loop=1" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/IHQgnpSphEI?start=27&autoplay=1&mute=1&loop=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</section>
<section>
<h2>Historical perspective</h2>
<br />
<ul>
<li>Evolutionary Strategies</li>
<ul>
<li>developed by Rechenberg, Schwefel, etc. in 1960s</li>
<li>focus: real-valued parameter optimization</li>
</ul>
<li>Evolutionary Programming</li>
<ul>
<li>developed by Fogel et al in 1960s</li>
<li>focus: evolve intelligent behavior with Finite State Machines</li>
</ul>
<li>Genetic Algorithms</li>
<ul>
<li>developed by Holland in 1960s</li>
<li>focus: robust, adaptive systems, reproduction via mutation and recombination</li>
</ul>
<li>Genetic Programming</li>
<ul>
<li>developed by Koza in 1988</li>
<li>focus: evolution of programs</li>
</ul>
</ul>
</section>
<section>
<h2>Applications</h2>
<br/>
<ul>
<li>Software design</li>
<li>Robotics and hardware design</li>
<li>Biology and bioinformatics</li>
<li>Management, scheduling</li>
<li>Economics, trading systems</li>
<li><a href="https://en.wikipedia.org/wiki/List_of_genetic_algorithm_applications">and more</a></li>
</ul>
<br/>
<br/>
<img src="../imgs/antenna.jpg">
</section>
<section>
<h2>Well-known algorithms</h2>
<br/>
<ul>
<li>CMA-ES</li>
<ul>
<li>Covariance Matrix Adaptation Evolutionary Strategy</li>
<li>Continuous optimization</li>
</ul>
<li>NSGA-II</li>
<ul>
<li>Non-dominated Sorting Genetic Algorithm II</li>
<li>Multi-objective optimization</li>
</ul>
<li>NEAT</li>
<ul>
<li>Neuroevolution of Augmenting Topologies</li>
<li>Evolution of neural networks</li>
</ul>
<li>MAP-Elites</li>
<ul>
<li>Illuminating Search Spaces by Mapping Elites</li>
<li>Evolution of behavior</li>
</ul>
</ul>
<img src="../imgs/cmaes.png" width="40%" height="auto">
</section>
<section>
<h2>Resources</h2>
<br/>
Evolutionary computation methods in many languages
<br/>
<br/>
<ul>
<li><a href="https://cs.gmu.edu/~eclab/projects/ecj/">ECJ</a>: very mature, general framework, Java</li>
<li><a href="http://gplab.sourceforge.net/">GPLAB</a>: genetic programming, MATLAB</li>
<li><a href="http://www.mathworks.com/products/global-optimization/index.html">Optimization Toolbox</a>: implements genetic algorithm, MATLAB</li>
<li><a href="https://github.com/CMA-ES/pycma">pycma</a>: CMA-ES, Python</li>
<li><a href="https://pymoo.org/">pymoo</a>: Multi-objective, Python</li>
<li><a href="https://github.com/chgagne/beagle">BEAGLE</a>: framework, C++</li>
<li><a href="https://github.com/Hintzelab/MABE">MABE</a>: new framework, C++</li>
<li><a href="https://github.com/MaxHalford/eaopt">eaopt</a>: new generic, Go</li>
</ul>
<br/>
<br/>
and many many more
</section>
<section>
<h2>In this class</h2>
<ol>
<li><b>Genetic Algorithms</b>: Mutation, Crossover, TSP</li>
<li><b>Evolutionary Algorithms</b>: 1+1, 1+lambda</li>
<li><b>Evolutionary Strategies</b>: Continuous optimization</li>
<li><b>Neuroevolution</b>: Neural network optimization with ES</li>
<li><b>Multi-Objective Optimization</b>: NSGA-II</li>
<li><b>Behavior and Novelty</b>: behavioral diversity, novelty search and
Quality Diversity</li>
<li><b>Genetic Programming</b>: Tree-based representation</li>
<li><b>Symbolic Regression</b>: Data function optimization</li>
</ol>
<br/>
<br/>
<a href="https://evolutiongym.github.io/">Evogym</a> project: Form and policy
<br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/VWivmi9j608" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
</section>
<section>
<h2>Not in this class</h2>
<br/>
<ul>
<li><a href="https://en.wikipedia.org/wiki/Estimation_of_distribution_algorithm">Estimation of distribution algorithms</a></li>
<li><a href="https://en.wikipedia.org/wiki/Evolutionary_programming">Evolutionary Programming</a></li>
<li><a href="https://en.wikipedia.org/wiki/Artificial_immune_system">Artificial Immune Systems</a></li>
<li><a href="https://en.wikipedia.org/wiki/Learning_classifier_system">Learning Classifier Systems</a></li>
<li><a href="https://en.wikipedia.org/wiki/Surrogate_model">Surrogate models</a></li>
<li><a href="https://en.wikipedia.org/wiki/Swarm_intelligence">Swarm intelligence</a></li>
<li><a href="https://en.wikipedia.org/wiki/Particle_swarm_optimization">Particle Swarm Optimization</a></li>
<li><a href="https://en.wikipedia.org/wiki/Simulated_annealing">Simulated annealing</a></li>
</ul>
<br/>
<br/>
<div class="textbox">
The GECCO (Genetic and Evolutionary Computation Conference) <a href="https://dl.acm.org/doi/proceedings/10.1145/3205651">Proceedings</a> include excellent tutorials on many of these subjects for further reading.
</div>
</section>
<section>
<h2>Exercise</h2>
<br/>
<br/>
Break into groups and discuss:
<br/>
<br/>
<div class="textbox">
What drives selection in biological evolution? Can these selection pressures be expressed, quantified, or measured? How can we replicate selection pressures in artificial evolution?
</div>
<br/>
</section>
</div>
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<div id="footer">
Evolutionary Computation by Dennis G. Wilson, Yuri Lavinas, Paul Templier
<br />
<a href="https://github.com/d9w/evolution/">https://github.com/d9w/evolution/</a>
<br />
<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/80x15.png" /></a>
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