Evolving to predict [data]
If one thinks that biological evolution is infinitely powerful one might imagine that by emulating it one would always be able to find ways to predict any sequence of data. But in practice methods based, for example, on genetic programming seem to do at best only about as well as all sorts of other methods discussed in this chapter. And typically what limits them seems to be much the same as I argue in Chapter 8 limits actual biological evolution: that incremental changes are difficult to make except when the behavior is fairly simple. (See also page 985.)
It is common for animals to move in apparently random ways when they are trying to avoid predators. Yet I suspect that the randomness they use is often generated by quite simple rules (see page 1011)—so that in principle it could be predictable. So it is then notable that biological evolution has apparently never made predators able to catch their prey by predicting anything that looks to us particularly random; instead strategies tend to be based on tricks that do not require predicting more than at most repetition.