The DARPA race and Probabilistic AI

This article covering the DARPA Grand Challenge road race in the NY Times interested me for more reasons than one -- the biggest one of 'em all being the advances made in 'probabilistic' AI. While I would acknowledge the contributions logic-based AI has made so far, I do not think that it is the way to go. Probabilistic decision making techniques are more representative of the way in which humans function in their environments, and developing computational techniques that can simulate these will mean huge advances in AI. However, the obstacles still remain...

Here's a snippet from the article -

While artificial intelligence technology is already in use in telephone answering systems with speech recognition and in popular household gadgets like the iRobot vacuum cleaner, none of the existing systems have been as ambitious as Darpa's Grand Challenge road race.

This leap was possible, in large part, because researchers are moving from an approach that relied principally on logic and rule-based systems to more probability or statistics-oriented software technologies.

"In the past A.I. has been dominated by symbolic systems and now the world is gray," said Terrence J. Sejnowski, head of the computational neurobiology laboratory at the Salk Institute in La Jolla, Calif. "That's what it's like to deal with the real world."

This crucial shift, Mr. Sejnowski said, "grew out of the recognition that the human brain is very good at this, why not have machines do the same thing?"

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