Evolutionary Robotics and Open-Ended Design Automation

Evolutionary Robotics and Open-Ended Design Automation
Hod Lipson, Cornell University Can a computer ultimately augment or replace human invention? IMAGINE A LEGO SET AT YOUR DISPOSAL: Bricks, rods, wheels, motors, sensors and logic are your “atomic” building blocks, and you must find a way to put them together to achieve a given high-level functionality: A machine that can move itself, say. You know the physics of the individual components ' behaviors; you know the repertoire of pieces available, and you know how they are allowed to connect. But how do you determine the combination that gives you the desired functionality? This is the problem of Synthesis. Although engineers practice it and teach it all the time, we do not have a formal model of how open-ended synthesis can be done automatically. Applications are numerous. This is the meta-problem of engineering: Design a machine that can design other machines. The example above is confined to electromechanics, but similar synthesis challenges occur in almost all engineering disciplines: Circuits, software, structures, robotics, control, and MEMS, to name a few. Are there fundamental properties of design synthesis that cut across engineering fields? Can a computer ultimately augment or replace human invention? While we may not know how to synthesize thing automatically, nature may give us some clues: After all, the fascinating products of nature were designed and fabricated autonomously.

Introduction
In the last two centuries, engineering sciences have made remarkable progress in the ability to analyze and predict physical phenomena. We understand the governing equations of thermodynamics, elastics, fluid flow, and electromagnetics, to name but a few domains. Numerical methods such as finite elements allow us to solve these differential equations, with good approximation, for many practical situations. We can use these methods to investigate and explain observations, as well as to predict the behavior of

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