Human-Assisted

Tetsuo Tomiyama Faculty of Mechanical, Maritime and Materials Engineering Delft University of Technology Delft, The Netherlands "(...) 1.2. Intelligent CAD: Next 20 years The goal of intelligent CAD to automate design was almost a mission impossible, and the dream of intelligent CAD as a system started to die already perhaps in the middle of the 1990s, although I strongly believe that the concepts are still valid and still exist as a vision for a number of reasons. There are two major concepts of intelligent CAD. One is related to the original goal of intelligent CAD, which is the intensive use of design knowledge to design artifacts in one way or another. The other is related to the second goal, which is that intelligent CAD should exhibit knowledge management capabilities because design is mostly a knowledge generation process. These two concepts were gradually incorporated into commercial CAD platforms over the last 20 years. For example, knowledge representation in the form

'The inventor’s trial-and-error approach can be automated by software that mimics natural selection “I have not failed. I have just found 10,000 ways that won’t work.” So said Thomas Edison, the prolific inventor, speaking of his laborious attempts to perfect the incandescent light bulb. Although 10,000 trial-and-error attempts might sound a little over the top, an emerging technique for developing inventions knocks even Edison’s exhaustive approach into a cocked hat. Evolutionary design, as it is known, allows a computer to run through tens of millions of variations on an invention until it hits on the best solution to a problem. As its name suggests, evolutionary design borrows its ideas from biology. It takes a basic blueprint and mutates it in a bid to improve it without human input. As in biology, most mutations are worse than the original. But a few are better, and these are used to create the next generation. Evolutionary design uses a computer program called an evolutiona

Here Manuel DeLanda, a Mexican artist and writer, makes his description of possible uses of genetic algorithms (GA's) in building architecture. It forms part of my research and I include it in this article under the doctrine of fair use [copyright.gov]. DeLanda envisions future work with GA's in building architecture as necessarily an architectmachine co-dependence affair. My first-hand research on GA's, and trends on GA use makes me view DeLanda's escenario of people breeding their own buildings, without a professional's intervention as the more realistic -and desirable!- alternative. DeLanda's limitation in his grasp of GA's is illustrated by his belief that such an algorithm's success in automatically generating designs for habitable structures depends on an "adequate diagram" or "abstract building" provided by a human. This belief is analogous to suggesting horse carriage designers provided mechanical engineers with an adequate