More on drift
Looking at more best-agent vs last-agent-in-search comparisons today has made me realise something: the one pattern that seems to be emerging is that the last agent tends to be much more consistent in its behaviour than the agent from 1000 generations earlier. They achieve this by being less affected by sensory input, though looking at their genotypes is not enlightening as regards exactly how, so it's nothing as straightforward as the setting of gains to 0 that I saw with the catcher agent.
On a given batch of trials, this often (but not consistently) causes a marginal improvement in the agent's performance, yet in the search this never registered as an increase in fitness. This seems to be because the 'best' agent in a search is actually the agent that gets luckiest in terms of the exact batch of trials it encounters, so on the particular batch that's in use in its generation it actually benefits from the noise. But then, when I compare it to other agents using a standardised batch of trials, it's very unlikely that this batch will happen to favour it like the one it encountered during evolution. Of course, the fitness improvements I'm seeing are all very small (typically in the third significant figure), because if they were bigger then they would swamp the randomness effect, and we'd have a new 'best agent'.
Anyway, the upshot of this is that I'm not sure what's happening really counts as random drift, because there seems to have still been some fitness improvement.
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