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". 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/
