Researchers from Penn State have received $900,000 to teach computers how to generate original design ideas and then determine if those ideas are technically feasible. The Defense Advanced Research Projects Agency (DARPA) is supporting the 18-month project.

“We are trying to determine if we can train a computer to do multiple things,” explained Conrad Tucker, associate professor of engineering design and industrial engineering, who is a co-principal investigator (PI) on the project. “First, we want to train a computer to generate novel engineering design ideas, and then we want to train it to determine whether or not those generated ideas make any sense in the real world.”

The domain of deep learning that the researchers are exploring is called generative adversarial networks (GAN). GANs consist of two competing neural networks: one is generating ideas and the other is discriminating to determine if the idea makes any sense.

In order to be able to create the discriminator network, the research team is proposing to use simulation environments (i.e. similar to those used in virtual reality) to embed knowledge about physics and physical properties of the universe so that as designs are generated, they are grounded in the physical laws that govern the universe.

Graduate students Matt Dering (computer science), James Cunningham (computer science) and Kevin Lesniak (industrial engineering), along with several undergraduate engineering students, are assisting on the project, according to a statement by the university.

[Image courtesy: Penn State]