The idea is that a human, contrary to the computer, has the idea of "worthless" moves and a special preselection. So a grandmaster only considers the "good" moves (of which there are maybe 5 or 10), while the computer has to scan through all possible moves and rate them to even find out what "good" moves are. Vast libraries for the opening help the computer reduce the initial tree of possible moves down to a set of "traditional" moves.

Another side point might make this phenomenon more plausible to you :
If you show chessboards with regular play situations on them for a short time to people, those who play chess will more accurately reconstruct the board than those who don't. But if you show them pieces randomly placed on a board, both groups will show a similar rate of errors. This could be interpreted that the human does not see the places of all pieces on the board separately but in relation to the other figures, remembering patterns he has seen/experienced (in play) before.

A game that solely relies on patterns and their recognition is Go, a game that is considered very hard to write computer opponents for.

perl -MHTTP::Daemon -MHTTP::Response -MLWP::Simple -e ' ;    # The  
$d = new HTTP::Daemon and fork and getprint $d->url and exit;#spider
($c = $d->accept())->get_request(); $c->send_response( new   #in the
HTTP::Response(200,$_,$_,qq(Just another Perl hacker\n))); ' #  web
[download]

The idea is that a human, contrary to the computer, has the idea of "worthless" moves and a special preselection

I am going to bow out of this now, because all the responses are now devolving to "humans do something, we don't know what, but it ain't what computers do". This is not proof or reasonable support, but merely the naysaying of something.

What reasonable support do you want? Grandmasters *have* been questioned and observed. It *is* know what they do (examine just a few number of moves), we don't know how exactly they select the moves to examine. What they certainly do know is that they don't examine all the positions a computer examines. And there's a simple proof: take a random grandmaster, playing a random game. Measure the time it takes to make a move. The average of those times is less than 50 years. qed. There's no magic, handwaving or naysaying going on.

Just because you don't know everything doesn't mean you cannot exclude everything. Suppose I know X was in a house. I don't watch the house, but I do watch the road going south from the house. Now, X is no longer in the house. According to your reasoning saying "I don't know where X went, but I know he didn't go south" is not a proof or reasonable support, but merely naysaying of something, because I don't know where X went.

But have you presented any proof or reasonable support that how computers play chess has any similarity to how humans do?

Abigail

This hardly points at some difference in heuristics betwee

Humans aren't slightly better than computers at chess (and much better than computers at go) because they analyze more moves. On the contrary: they're better despite analyzing only an insignificant number of moves!

Okay, we don't "know" how humans make this pre-selection; does it matter? does the mechanism with which the selection is made determine whether it is the exhibition of intelligence? Or is the ability to make the selection and decision the exhibition of intelligence?

If it is the mechanism which is the difference and we don't know what that mechanism is, then how can you state that the mechanism used in AI is shallow or unsatisfactory for the problem set?

Abigail