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Unfortunately, your intelligent agents qualify as optimization algorithms and therefore the No Free Lunch Theorem applies:

I.e. across the space of all possible environments, all agents perform equally well

As others pointed out, the NFLT only applies if the environments are uniformly distributed. In the paper, they are not uniformly distributed.

I missed your post and I made a similar answer.

However the idea may still be applicable if the environments votes can weighted, based on their relevance to specific domains.

(The same way optimization techniques are still useful despite the NFTL)