>> To give an example, what if the algorithm is to generate the correct algorithm?
That's not a description of an algorithm. You've stated a "problem". An algorithm, by definition, is an actual deterministic procedure.
That's not a description of an algorithm. You've stated a "problem". An algorithm, by definition, is an actual deterministic procedure.
I wanted to say the same thing, but you managed to find the words I couldn't.
> An algorithm, by definition, is an actual deterministic procedure
That's not necessarily true. There are non-deterministic algorithms: https://en.wikipedia.org/wiki/Nondeterministic_algorithm
Well they can. Quantum computers are inherently non-deterministic.
Even for a classical computer, access to a true randomness source (such as a sufficiently good hardware RNG) is enough to make a classical computer non-deterministic, and hence programs that rely on that true randomness source are classified as non-deterministic.
In practice, we sometimes classify a program as nondeterministic even if it only has access to pseudorandomness, provided that pseudorandomness is "random enough". If a program uses a high quality PRNG seeded with the current time, that might be practically considered non-deterministic, even though strictly speaking the program's behaviour is a deterministic function of the current time (and other inputs).
Are you tautologically saying “determinism is determinism” because you define an algorithm as a “deterministic procedure”.
Biological neural networks are non-deterministic.
(You can debate philosophically whether apparent non-determinism is actually fundamentally non-deterministic or ultimately reduces to some hidden determinism. It depends on one's choice of interpretation of quantum theory – many worlds and hidden variables both claim that reality is fundamentally deterministic, other interpretations do not. But, whether or not non-determinism ultimately exists, it certainly apparently exists, both in biological and technological systems.)