Color Sudoku game adds twist to computing

New visual tools
Although not designed to yield definitive answers, the Clayton Tunnel exercise has nonetheless suggested that systemic problems may have arisen from the introduction of new technology and that the accident’s cause was not limited to human error alone. Likewise, Russ said, the integrative approach of Empirical Modelling recommends itself for improving the safety of modern systems that require human involvement and as a platform for more imaginative pursuits.

Among the dozens of departmental student projects available for downloading from the research group’s site, one simulates the buildup of traffic behind three traffic lights at a T junction. Another offers a simulated environment for practicing how to park a car, complete with steering wheel and pedal. And a third attempts to realistically model how ants navigate, focusing in particular on their visual cues and use of landmarks.

Using the same approach, project leader Meurig Beynon has created a kind of visual map for Franz Schubert’s musical adaptation of a dramatic poem called “Erlkönig,” challenging conventional associations between mathematics and music in the process. With one color-coded band, Beynon marked out different characters’ actions within the song, while a second symbolized the changing musical keys and harmonies. Traditional mathematical-based representations of a song often link its cycle of keys to a color wheel, with the ends of spokes corresponding to different keys.

Empirical Modelling, by contrast, allowed Beynon to create a flexible version of the wheel that could be distorted to accommodate Schubert’s unusual tendency to blend incongruous keys such as C major and C minor — keys normally kept far apart. The resulting visual display can be synched to a performance of the song, presenting a blend of the computer’s automatic associations and Beynon’s subjective choices — and perhaps, offering a new tool to gauge how people perceive music.

Redefining computer science
The open and exploratory nature of Empirical Modelling can have its downside. “We find it very hard, on the whole, to communicate with traditional computer scientists,” Russ said. “They want everything to be very formal and are suspicious when we say that we haven’t got a formal notation for something.”

Willard McCarty, a professor at the Centre for Computing in the Humanities at King’s College in London, said part of the miscommunication may stem from the lack of a common language among the widely disparate arms of computer science. And unlike its academic cousins, he said, Empirical Modelling is far more improvisational, with no pre-determined idea of what might happen. “You’re creating something that doesn’t yet exist, for which there are no plans or models,” he said.

Although McCarty hailed the Warwick group for breaking the mold, he conceded that such admiration has been far from universal. “They have existed in a semi-hostile environment for many years,” he said. “What they’re trying to do is redefine computer science to venture into the area of creative activity, and that’s a very risky thing to do.”

Ultimately, he believes the gambit will pay off, with the potential to benefit research delving into open-ended questions in fields such as childhood learning and developmental psychology. The history of invention, after all, is filled with “people who really didn’t know what they were going to find; they were just fiddling with materials,” McCarty said.

What they did have, he said, was a good medium for channeling their creativity — something that Empirical Modelling may yet become.

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