Response to the review of "Variation-Aware Analog Structural Synthesis: A Computational Intelligence Approach"

Trent McConaghy, coauthor of Variation-Aware Analog Structural Synthesis: A Computational Intelligence Approach, wrote a response to the review of the book in Genetic Programming and Evolvable Machines and I have agreed to publish his response here. Trent's letter follows:

In the December issue of Genetic Programming and Evolvable Machines (volume 12:4), John Rieffel gave a review of the book "Variation-Aware Analog Structural Synthesis: A Computational Intelligence Approach", of which I was a co-author.  

We would like to express our thanks to John for a thoughtful review, covering the reliable and trustworthy approaches to perform industrially-oriented symbolic regression, robust optimization, and analog structural synthesis.  

We would like to clarify one point: while the review reports that the book ignores "simulators that cheat", the book in fact dedicates substantial space on this issue, and how open-ended synthesis approaches are highly prone to it.  (See pp. 157-167, including the section "SPICE can lie".)

The broader issue -- trustworthy synthesis -- is a broad challenge that the last half of the book addresses.  Trustworthy synthesis outputs circuits that a designer trusts enough to commit to silicon.  The book proposes to use hierarchical building blocks developed over the decades by expert designers, enabling synthesis to output circuits that are trustworthy by construction.

As the book discusses, the computational intelligence techniques presented generalize beyond analog CAD, to domains such as robotics, financial engineering, mechanical design, and more.  

 -- Trent McConaghy, October 3, 2011