On Fri, Mar 20, 2015 at 8:24 PM, Hugh Perkins <hughperk...@gmail.com> wrote:
> On 1/12/15, Álvaro Begué <alvaro.be...@gmail.com> wrote: > > A CNN that starts with a board and returns a single number will typically > > have a few fully-connected layers at the end. You could make the komi an > > extra input in the first one of those layers, or perhaps in each of them. > > That's an interesting idea. But then, the komi wont really > participate in the hierarchical representation we are hoping that the > network will build, that I suppose we are hoping is the key to > obtaining human-comparable results? > I don't see why komi needs to participate in the hierarchical representation at all. The representation is supposed to learn higher-level notions like good shape, life and death, territory... The effect of komi can easily be incorporated into the mix at a later stage, since it has no bearing on what's good shape, what's alive or dead or what constitutes territory. On Fri, Mar 20, 2015 at 8:24 PM, Hugh Perkins <hughperk...@gmail.com> wrote: > On 1/12/15, Álvaro Begué <alvaro.be...@gmail.com> wrote: > > A CNN that starts with a board and returns a single number will typically > > have a few fully-connected layers at the end. You could make the komi an > > extra input in the first one of those layers, or perhaps in each of them. > > That's an interesting idea. But then, the komi wont really > participate in the hierarchical representation we are hoping that the > network will build, that I suppose we are hoping is the key to > obtaining human-comparable results? > > But on the other hand, in the general case, where we want to give a > variety of inputs to the computer, eg a map, and an x/y position, has > anyone come up with a clean, effective way of combining these inputs > into the net? I dont recall seeing any such attempt/paper? > - if we feed the map into a conv net, and the x/y pos into the fc > layers, it seems like the x/y pos wont really participate in any > hierarchical representation? > - if we have 100 conv input planes for each possible value of x, and > another 100 for each possible value of y, seems like overkill ... ? > - feeding reals into neural nets, which have layered activation > functions, empirically doesnt work well, and logically doesnt sound > like it should work that well > - contemplating just feeding them in as visual representations of the > number, printed each on a single plane :-D > > Are there some papers/research/approaches in the area of combining > non-image inputs into convnets, in such a way that the non-image > inputs participate in the hierarchical structure, and at the same > without creating hundreds of input planes, for each single natural > input, which planes might contain only 5-10 bits of actual > information? > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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