This is really cool. Now it just needs to learn 9x9 via reinforcement
learning ;-)
Josef Moudrik <j.moud...@gmail.com> schrieb am Fr., 18. März 2016 10:21:
> Aha! Thanks for the clarification.
>
> Josef
>
> Dne pá 18. 3. 2016 9:59 uživatel Darren Cook <dar...@dcook.org> napsal:
>
>> > If I remember correctly, it is not browser implementation, but rather a
>> > frontend. The actual computation runs on server, browser only
>> communicates the
>> > moves and shows the results.
>>
>> No, a quick test shows once it loads it has not made any server calls.
>> It has a 14MB file which looks like [1]
>>
>> Darren
>>
>>
>> [1]:
>> // 8 layer network trained on GoGoD data, truncated to 6 decimal places
>> to reduce size
>> var json_net = {"layers": [{"layer_type": "input", "out_sy": 25,
>> "out_depth": 8, "out_sx": 25}, {"layer_type"
>> : "conv", "sy": 25, "sx": 25, "out_sx": 19, "out_sy": 19, "stride": 1,
>> "pad": 0, "biases": {"depth":
>> 64, "sx": 1, "sy": 1, "w": [0.519023, -1.379795, -0.495255, -0.051380,
>> -0.466160, -1.380873, -0.630742
>> , -0.174662, -0.743714, -1.288785, -0.607110, -0.536119, -0.819585,
>> -0.248130, -0.629681, -0.004683,
>> -0.408890, -1.701742, -0.011255, -0.833270, -0.665327, -0.127002,
>> -0.793772, -0.518614, -1.390844, -1
>> .982825, -0.012530, -0.140848, -1.255086, -0.761665, -0.077154,
>> -0.748323, -0.086952, -0.175683, -1.526860
>> , 0.098685, -0.030402, -0.903232, -
>> ...
>>
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