Guys, please take a day. steve On Mar 30, 2016 1:52 PM, "Brian Sheppard" <sheppar...@aol.com> wrote:
> Trouble is that it is very difficult to put certain concepts into > mathematics. For instance: “well, I tried to find parameters that did a > better job of minimizing that error function, but eventually I lost > patience.” :-) > > > > Neural network parameters are not directly humanly understandable. They > just happen to minimize an error function on a sample of training cases > that might not even be representative. So you want to reason “around” the > NN by interrogating it in some way, and trying to explain the results. > > > > If anyone wants to pursue this research, I suggest several avenues. > > > > First, you could differentiate the output with respect to each input to > determine the aspects of the position that weigh on the result most > heavily. Then, assuming that you can compare the scale of the inputs in > some way, and assuming that the inputs are something that is understandable > in the problem domain, maybe you can construct an explanation. > > > > Second, you could construct a set of hypothetical different similar > positions, and see how those results differ. E.g., make a set of examples > by adding a black stone and a white stone to each empty point on the board, > or removing each existing stone from the board, and then evaluate the NN on > those cases, then do decision-tree induction to discover patterns. > > > > Third, in theory decision trees are just as powerful as NN (in that both > are asymptotically optimal learning systems), and it happens that decision > trees provide humanly understandable explanations for reasoning. So maybe > you can replace the NN with DT and have equally impressive performance, and > pick up human understandability as a side-effect. > > > > Actually, if anyone is interested in making computer go programs that do > not require GPUs and super-computers, then looking into DTs is advisable. > > > > Best, > > Brian > > > > > > *From:* Computer-go [mailto:computer-go-boun...@computer-go.org] *On > Behalf Of *Jim O'Flaherty > *Sent:* Wednesday, March 30, 2016 4:24 PM > *To:* computer-go@computer-go.org > *Subject:* Re: [Computer-go] new challenge for Go programmers > > > > I agree, "cannot" is too strong. But, values close enough to "extremely > difficult as to be unlikely" is why I used it. > > On Mar 30, 2016 11:12 AM, "Robert Jasiek" <jas...@snafu.de> wrote: > > On 30.03.2016 16:58, Jim O'Flaherty wrote: > > My own study says that we cannot top down include "English explanations" of > how the ANNs (Artificial Neural Networks, of which DCNN is just one type) > arrive a conclusions. > > > "cannot" is a strong word. I would use it only if it were proven > mathematically. > > -- > robert jasiek > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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