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Great point - they work well for anything where the optimization surface is relatively smooth, where small changes don't lead to highly suboptimal solutions. I
by etrautmann 11y ago
Great point - they work well for anything where the optimization surface is relatively smooth, where small changes don't lead to highly suboptimal solutions. In programming, a single character can make a program go from working to not, so the likelihood of "discovering" a valid program is low.
- api 11y agoThere's a whole subdomain of genetic programming research that centers around the design of evolvable computer languages and instruction encodings. There are some immensely interesting programming languages and instruction sets out there for which this is less true than for ordinary programming. But we still have yet to devise an encoding that is truly analog and smooth... except maybe for really exotic encodings that are too slow to be useful in any practical system. These are sort of like homomorphic crypto-- interesting but too compute intensive to run anything real.