If I knew the answers to those questions, I wouldn’t be asking mine .
I guess basically it’s just a hunch I had that TC/IC and working in a wicked problem framework—rather than (say) an optimizing one—might be productive. I think the root of that hunch lies in my target analysis background—there one can measure better or worse in terms of how quickly an algorithm picks up a target, how long you can track it in noise, how quickly you can identify it as a threat or not, that sort of thing. Everything is, in theory moderately knowable. Systems that work in the lab tend to work in practice, etc.
TC otoh doesn’t really seem to be the same. A big problem of course is that the target itself is unknown (except in a vague sort of way), and as of this moment I don’t have any sense whether an approach that’s good for this round will be at all valid the next. And of course there’s the feedback nature of the competition, which from a fairly simple Darwinian perspective might imply that good solutions will cluster, lessening the value of each. I really don’t know, these are just things to ponder.
All that said, I do like having a framework in which to approach complex problems. For example, right now (rounds 310 & 311) the Tournament I’ve just started running 50 models that might be more wicked problem type solutions; they’re built on a genetic algorithm that leans more towards survivability than achieving peak performance. Some of them are doing quite well, and the rest not so well What’s interesting is that they correlate to each other quite consistently, one group of 25 at about 0.1 among themselves, the other at about 0.7.I’m curious as to how they will sort themselves out over a number of runs.
Over in Signals, I have been running another 50 models that were (algorithmically) very tied together. They did ok on corr an MMC, an absolutely appallingly on IC. Except for two.and those two were the least tied to the rest.
So putting those experiences together leads me to think that trying to optimize for a best solution isn’t the right way to go. It may be better to evolve a set of solutions each of which performs moderately, but generally avoids getting murdered. Does that make sense?
In any case, I do things like this that spark my curiosity!