Once a robot is built, it may well be necessary to "fine-tune"' adaptation in the
real world. Our approach is to perform adaptation via a decentralized evolution-
ary algorithm that is distributed and embodied within a population of robots.
The distributed and asynchronous operation of this evolutionary method allows
the potential for being scaled to very large populations of robots, on the order of
hundreds or thousands, thus enabling speedup that is critical when using evolu-
tion in real robots.
Technologically, this introduces two
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