You're halfway there. What you describe is genetic algorithms in their classical implementation.
Here he uses a FPGA, a kind of processor that can be rewired at will, in hardware. The gates can be programmed into the various boolean operators you know, usually to implement a specialized binary processor (say, a DSP).
Binary here means that after a set amount of time set by a clock, every cell will either be in a ON (1) or OFF (0) state.
The researcher here uses genetic algorithms to find the best configuration of gates to perform the required task.
What's new here is that the fittest "program" doesn't work in a digital fashion like classical processors. It doesn't have a clock, and acts as an extremely minified electronic analogical circuit.
I'd love to see how this could be combined with hybrots...
Comments
You're halfway there. What you describe is genetic algorithms in their classical implementation.
Here he uses a FPGA, a kind of processor that can be rewired at will, in hardware. The gates can be programmed into the various boolean operators you know, usually to implement a specialized binary processor (say, a DSP).
Binary here means that after a set amount of time set by a clock, every cell will either be in a ON (1) or OFF (0) state.
The researcher here uses genetic algorithms to find the best configuration of gates to perform the required task.
What's new here is that the fittest "program" doesn't work in a digital fashion like classical processors. It doesn't have a clock, and acts as an extremely minified electronic analogical circuit.
I'd love to see how this could be combined with hybrots...
http://en.wikipedia.org/wiki/Hybrot