Hideki Kato: <4ad5e7f1.77%hideki_ka...@ybb.ne.jp>:
>Álvaro Begué: <7b0793ea0910140721l2819723bl12af6c1c3dd9...@mail.gmail.com>:
>>We should let go of this idea that artificial neural networks have
>>anything to do with the brain. ANNs are just a family of parametric
>>functions (often with too many parameters for their own good) and
>>associated tuning algorithms ("learning" is a bit pretentious).
>>Perhaps they took vague inspiration in a cartoonish version of the
>>brain, but that's about it.
>
>As I wrote before, if you want general purpose approximater, use RL
>or SVM which performs much better than ANNs.
>
>>People tried to make flying machines by imitating birds for a long
>>time. Planes and helicopters fly, but not like birds do it. Similarly,
>>I believe that whenever we figure out how to make machines that play
>>go well, they will not do it like a brain does it.
>
>There are so many flying objects in the worlds such as leaves,
>bats, bees, not only birds. People can observe and compare them and
>then extract the essence of "flying". This is not the case of
>"thought".
Just making things clearer, I'd like to change the word "thought"
here to "intelligence".
Hideki
>Moreover, if we really wants flying machines like birds, say, more
>silent, gentle and elegant, perhaps we have to observe birds more
>precisely. It's possible that thinking machines are the case.
>
>Hideki
>
>>Álvaro.
>>
>>
>>On Wed, Oct 14, 2009 at 10:00 AM, Hideki Kato <hideki_ka...@ybb.ne.jp> wrote:
>>> IMHO, when applying artificial neural networks to an application, the
>>> structure (as well as the learning algorithm) of the network is very
>>> important. For Go, we haven't invetigated the mechanism how the brain
>>> is used yet. Backpropagation-style layered network is just a model of
>>> the cerebellum and I strongly believe we need a higher-level model to
>>> replace the modern MCTS Go programs, say, how the cerebellum works
>>> together with the other areas of the brain (such as cerebrum and basal
>>> ganglia which is said working like RL) playing a game but it's not
>>> established nor proposed. If the model approximates the mechanism of
>>> real brain well enough, it never performs well.
>>>
>>> As a general purpose learning machine, neural networks perform much
>>> worse than sophisticated learning algorithms such as RL and also
>>> worse than suppoert vector machines, as Remi mentioned.
>>>
>>> Hideki
>>>
>>> Petr Baudis: <20091014122619.gu6...@machine.or.cz>:
>>>> Hi!
>>>>
>>>> Is there some "high-level reason" hypothesised about why there are
>>>>no successful programs using neural networks in Go?
>>>>
>>>> I'd also like to ask if someone has a research tip for some
>>>>interesting Go sub-problem that could make for a nice beginner neural
>>>>networks project.
>>>>
>>>> Thanks,
>>> --
>>> g...@nue.ci.i.u-tokyo.ac.jp (Kato)
>>> _______________________________________________
>>> computer-go mailing list
>>> computer-go@computer-go.org
>>> http://www.computer-go.org/mailman/listinfo/computer-go/
>>>
>>_______________________________________________
>>computer-go mailing list
>>computer-go@computer-go.org
>>http://www.computer-go.org/mailman/listinfo/computer-go/
>--
>g...@nue.ci.i.u-tokyo.ac.jp (Kato)
>_______________________________________________
>computer-go mailing list
>computer-go@computer-go.org
>http://www.computer-go.org/mailman/listinfo/computer-go/
--
g...@nue.ci.i.u-tokyo.ac.jp (Kato)
_______________________________________________
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/
