After trying for years to design a thinking computer, scientists working in artificial intelligence have a new approach. The best way to get a computer to think and behave like a human, a growing number of experts say, may be to let it evolve like one.
Artificial intelligence specialists are designing computer programs that apply principles of genetics and evolution to their own development, enabling the programs to grow, adapt and even fend off competition in a kind of virtual natural selection process, or "artificial life."
"The contrast is between building a robot. . . and letting it build itself," said Daniel C. Dennett, director of the Center for Cognitive Studies at Tufts University.
Programmers provide the "nature": a mathematical framework similar to the human genetic code. But in artificial life as in human life, nurture _ interaction with the environment _ plays a critical role in development.
In one program gaining attention in computer circles around Cambridge, Mass., for example, virtual "creatures" are placed in an environment where they must compete for symbolic "food" to survive.
The programmer, Karl Sims, formerly of Thinking Machines, gives the creatures several options, such as sprouting limbs to fend off rivals. But the entities choose among such options themselves, after testing to see what works best.
"It has to start the way a baby starts _ with a tremendous amount of design," Dennett said. "That's a big head start. But then, it's going to find out for itself all the things about how the world works."
"What we're really talking about here is learning," said Patrick H. Winston, director of MIT's Artificial Intelligence Laboratory.
In the past, artificial intelligence programs emphasized more straightforward programming, where information on how to "react" to any situation was fed to the computer. In artificial life, computers are given some leeway to change the shape and composition of their programs as they interact with the environment.
And there's growing conviction in computer science circles that this approach will produce machines with a rich, deep and versatile intelligence _ and perhaps, eventually, the ability to elude human control.
Because programmers will not dictate the step-by-step development of such machines, they also won't be entirely responsible for the ultimate product, said Dennett. "The smarter they get, the more impossible it will be to control them."
Versatile and autonomous thinking machines have been predicted before, of course. Artificial intelligence, first begun as a field in the '50s, was all the rage in the '80s as companies promised systems that would mimic the finest stock trader or the most nimble surgeon.
But most of those companies, many of them based in an area around Massachusetts Institute of Technology and Kendall Square in Cambridge known as "AI Alley," went bust. Artificial intelligence concepts could produce an excellent chess-playing computer or credit-card checker, but failed to meet expectations in more demanding applications.
These days, some regard artificial intelligence as a shopworn concept, a symbol of the unrealistic promises of those who breathlessly make predictions about technology.
Yet artificial intelligence is a quiet reality in the computer world in modest ways. So-called "expert systems," a kind of artificial intelligence, are embedded in personal computer software, whether spreadsheets or interactive card games.
Scientists at MIT's Artificial Intelligence Laboratory and elsewhere have not abandoned the goal of thinking machines. It is the path to that goal that has markedly changed _ from top-down programming to standing back and letting a hundred bits bloom.
"Artificial life is the next stage," said Harvey Newquist, author of the 1994 book "The Brain Makers" (MacMillan), which chronicled the rise and fall of AI companies. …