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Well, that's sort of the case for genetic algorithms. You might be aware of genetic programming? There may be papers already out there, but the idea is represe

Well, that's sort of the case for genetic algorithms. You might be aware of genetic programming? There may be papers already out there, but the idea is representing a programs source as a genome, and then performing the familiar processes (mutation, crossover, selection) on those. Anyhow, that would produce something more general. A genetic algorithm is traditionally a single shot thing.

UncleOxidant 6y ago
> You might be aware of genetic programming? Actually been playing with Cartesian Genetic Programming (CGP) recently. > Anyhow, that would produce something more general. Not really, at least as far as I can tell with CGP. I was evolving a circuit to solve the 8-bit parity problem (kind of the 'Hello world' of CGP - it solves this problem surprisingly quickly). There wasn't any way to use that information to evolve a circuit to solve the 16-bit parity problem - you've gotta start again from scratch. There may be some proposed solutions to this kind of issue in CGP - I'm still reading papers.
- adenozine 6y ago
  Ah, I see. I guess I meant general in the parameterization sense, not necessarily in the abstraction sense. Sorry, that could've been more clear. I've not dug into CGP yet, though I've read mentions of it. Would you perhaps have a good resource for learning? I'm a little weak on the math side.
  - UncleOxidant 6y ago
    > I'm a little weak on the math side. In general, I think that tends to one of the advantages of genetic algorithm/programming over neural nets/deep learning - the math is comparatively quite easy. This is the paper that introduced CGP by Julian Miller: https://thelackthereof.org/docs/library/cs/gp/Miller,%20Julian:%20Cartesian%20Genetic%20Programming.pdf https://thelackthereof.org/docs/library/cs/gp/Miller,%20Juli... I found this good survey of CGP here (from 2018): https://link.springer.com/content/pdf/10.1007/s10710-019-09360-6.pdf https://link.springer.com/content/pdf/10.1007/s10710-019-093...

UncleOxidant 6y ago

> You might be aware of genetic programming? Actually been playing with Cartesian Genetic Programming (CGP) recently. > Anyhow, that would produce something more general. Not really, at least as far as I can tell with CGP. I was evolving a circuit to solve the 8-bit parity problem (kind of the 'Hello world' of CGP - it solves this problem surprisingly quickly). There wasn't any way to use that information to evolve a circuit to solve the 16-bit parity problem - you've gotta start again from scratch. There may be some proposed solutions to this kind of issue in CGP - I'm still reading papers.

adenozine 6y ago
Ah, I see. I guess I meant general in the parameterization sense, not necessarily in the abstraction sense. Sorry, that could've been more clear. I've not dug into CGP yet, though I've read mentions of it. Would you perhaps have a good resource for learning? I'm a little weak on the math side.
- UncleOxidant 6y ago
  > I'm a little weak on the math side. In general, I think that tends to one of the advantages of genetic algorithm/programming over neural nets/deep learning - the math is comparatively quite easy. This is the paper that introduced CGP by Julian Miller: https://thelackthereof.org/docs/library/cs/gp/Miller,%20Julian:%20Cartesian%20Genetic%20Programming.pdf https://thelackthereof.org/docs/library/cs/gp/Miller,%20Juli... I found this good survey of CGP here (from 2018): https://link.springer.com/content/pdf/10.1007/s10710-019-09360-6.pdf https://link.springer.com/content/pdf/10.1007/s10710-019-093...