Tuesday, November 20, 2007

Evolving Computers

I read this article (from the Economist of all places!) a few years ago. It describes some 'turn of the century' stuff about using 'genetic algorithms' to allow computers to evolve their own solutions to problems presented to them. The program that does the job effectively gets to live and mate with other similar bits of code. In this case, the hardware was also programmable.

The article requires login, but i did find a copy of it here.

This is the best bit from it:

Dr Thompson performed a seminal "proof of principle" experiment which described the evolution in hardware of a simple analogue circuit that could discriminate between two different audio tones.

The type of chip that Dr Thompson selected to carry out the evolution was a field-programmable gate array (FPGA). Unlike an ordinary chip, an FPGA's architecture is not "hardwired". Instead of being fixed, a string of bits specifies the chip's design by telling it what linkages to forge between its various components (in this case, groups of transistors known as logic cells). By changing this bit string, the FPGA's circuitry can be altered on the fly. Thus, when a genetic algorithm runs on the chip, the effectiveness of each configuration can be measured directly on the circuit rather than in some costly simulation.

As it turned out, conducting the evolution in hardware produced some results that could not have emerged through mere simulation. After around 4,000 generations of bit strings, a unique circuit emerged. The surprising thing was that, while the new circuit relied directly on only a few of the FPGA's logic cells, it appeared somehow to take advantage of clusters of other cells nearby. These unconnected neighbouring cells could not be removed without damaging the circuit's performance. Further investigations revealed that these detached cells exerted some subtle electromagnetic influence on the wired-up part of the circuit, allowing it to perform its task efficiently.

Remarkably, the circuit had adapted itself in a way that allowed it to exploit the underlying physics of the FPGA's semiconductor material. And it had done this despite the fact that the human experimenters were completely unaware of the physical quirks in the semiconductor that the genetic algorithm was taking advantage of.

Four years on, this bizarre circuit has still not been completely
deciphered. What has become clear, however, is that EHW's ability to adapt automatically means that it can exploit the physics of materials in ways that researchers do not even consider, let alone

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