|Natural Law Recognition Machines
By Bill Steele
If Isaac Newton had access to a supercomputer, he'd have had it watch apples fall and let it figure out what that meant. But the computer would have needed to run an algorithm that can derive natural laws from observed data.
Researchers at Cornell University have taught a computer to find regularities in the natural world that represent natural laws -- without any prior scientific knowledge on the part of the computer. They have tested their method, or algorithm, on simple mechanical systems and believe it could be applied to more complex systems ranging from biology to cosmology and be useful in analyzing the mountains of data generated by modern experiments that use electronic data collection.
"Even though it looks like it's changing erratically, there is always something deeper there that is always constant," enginerring professor Hod Lipson explained. "That's the hint to the underlying physics. You want something that doesn't change, but the relationship between the variables in it changes in a way that's similar to [what we see in] the real system."
Once the invariants are found, potentially all equations describing the system are available: "All equations regarding a system must fit into and satisfy the invariants," said graduate student Michael Schmidt, a specialist in computational biology. "But of course we still need a human interpreter to take this step."
The researchers point out that the computer evolves these laws without any prior knowledge of physics, kinematics or geometry. But evolution takes time. On a parallel computer with 32 processors, simple linear motion could be analyzed in a few minutes, but the complex double pendulum required 30 to 40 hours of computation. The researchers found that seeding the complex pendulum problem with terms from equations for the simple pendulum cut processing time to seven or eight hours. This "bootstrapping," they said, is similar to the way human scientists build on previous work.
Computers will not make scientists obsolete, the researchers conclude. Rather, they said, the computer can take over the grunt work, helping scientists focus quickly on the interesting phenomena and interpret their meaning.
Their research is described in the April 3 issue of the journal Science (Vol. 323, No. 5924).
Source: Cornell University
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