Álvaro, When I say "think like a human player ", I mean regarding to the strategy. For example, when there are several fights happening simultaneously at the board, a human player can identify them and decide which one worth more to invest, I thinks this is a really difficult task in Go. How does he do this judge ? Which features does he analyze? And there are cases which "try" to mimic the biological solution is worth. See Neural Networks, Ant Colony Optimization Algorithm, Genetic Algorithm, etc.
Santos, Gabriel. On Mon, Apr 1, 2013 at 2:30 PM, Álvaro Begué <[email protected]> wrote: > > On Mon, Apr 1, 2013 at 11:10 AM, Gabriel .Santos <[email protected] > > wrote: > >> I know that it is a lot of questions, but in order to get a computer go >> machine to outperform a human player I think that the machine should to >> ratiocinate like a human player. > > > > Do you also think a machine that carries people very fast should have > strong legs like a horse? And a machine that can fly should flap its wings > like a bird? And a closer example: Do you think the same thing about chess > machines? > > In all those cases the engineering solution to the problem was very > different from the biological solution, and I expect the same will happen > with computer go. Actually, it's already happening. > > Álvaro. > > > > _______________________________________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go >
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