this is also interesting, to visualize "how the NN thinks"

http://blog.acolyer.org/2016/03/02/graying-the-black-box-understanding-dqns/

On Wed, Mar 30, 2016 at 10:38 PM, Ben <ben_computer...@hemio.de> wrote:

> It would be very interesting to see what these go playing neural networks
> dream about [1]. Admittedly it does not explain any specific moves the AI
> does - but it might show some interesting patterns that are encoded in the
> NN and might even give some insight into "how the NN thinks".
>
> Put differently: select a single neuron and find a board pattern such that
> the excitation of this neuron is maximal. With some luck you might be able
> to give meaning to this individual neuron or to single layers of the
> network (like how the first layers in pattern recognition basically detect
> edges).
>
>
> ~ Ben
>
> [1]
> http://googleresearch.blogspot.de/2015/06/inceptionism-going-deeper-into-neural.html
>
>
> Am 30.03.2016 22:23, schrieb Jim O'Flaherty:
>
>> 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
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>>
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