We're suffering under the burden of so much success from other methods that it's hard for many people to imagine that anything else is worth considering.
Of course this is not true. Tromp's enumerations are particularly enjoyable for me. Human-built decision trees have been so unsuccessful, compared with machine-learned models, for around 25 years, that only a few tiny wisps of academia are interested in them in a serious way that industry can and should take seriously. Some control-system methods, some ILP, some NLP, etc., are all successful counterexamples, in many cases in the field of logistics, transportation, etc. Complicated games such as go have pretty much not fallen due to these methods. (As a coworker of mine said recently, "It's probably going to be okay to hard-code the rule for the self-driving car not to hit pedestrians; there's no need to train with lots of examples of hitting pedestrians to train your algorithm".) They (analytically exact methods) are still interesting to study from a game-theoretic persepective, mathematically. There are exact solvers for all kinds of specialized problems. Problems with more than a few variables can very easily lead to many or most cases not being exactly (analytically) soluble. That's why all of these probabilistic approximation methods are so successful. They don't have to be exactly right. It's easing the constraint most people care least about (exact certitude of a win or success locally rather than an extremely high probability of a win or success locally). Asking the "high probability of success" guys to explain why their method works is a particularly galling (and trite) way of messing with them. They can just point to the results. The reason is that they don't know. And it's going to be a very, very long time before they do. At a fundamental level, probabilistic methods seem to be (some theoreticians believe) more powerful than non-probabilistic methods for relatively hard (as opposed to very very hard) problems. This is nicely encoded by computational complexity theorists as the question BPP = P ? steve On Tue, Oct 24, 2017 at 1:41 PM, Robert Jasiek <jas...@snafu.de> wrote: > On 24.10.2017 20:19, Xavier Combelle wrote: > >> totally unrelated >> > > No, because a) software must also be evaluated and can by go theory and b) > software can be built on exact go theory. That currently (b) is unpopular > does not mean unrelated. > > -- > robert jasiek > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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