Scalable Optimization Via Probabilistic Modeling: From Algorithms to Applications

✍ Scribed by Martin Pelikan, Kumara Sastry, Erick Cantú-Paz

Publisher: Springer
Year: 2006
Tongue: English
Leaves: 362
Series: Studies in Computational Intelligence
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book focuses like a laser beam on one of the hottest topics in evolutionary computation over the last decade or so: estimation of distribution algorithms (EDAs). EDAs are an important current technique that is leading to breakthroughs in genetic and evolutionary computation and in optimization more generally. I'm putting Scalable Optimization via Probabilistic Modeling in a prominent place in my library, and I urge you to do so as well. This volume summarizes the state of the art at the same time it points to where that art is going. Buy it, read it, and take its lessons to heart.

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