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2. Philosophy - Stefano Franchi

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206<br />

C HESS, GAMES, AND FLIES<br />

best] is precisely what human players do: no one plays a perfect game,” he says. Therefore,<br />

the “solution” of the game of chess might be found in the human way of playing chess and,<br />

on the reverse, the performance of a chess-playing computer may be measured against hu-<br />

man performance.<br />

This last point, however, is still a hint in Shannon’s paper and will not receive its full<br />

development until the works of Simon and Newell. What, on the other hand, seems un-<br />

doubtedly his, is the “discovery” of the combinatorial explosion of states as the result of the<br />

dynamic application of the rules. Although this may seem quite a discouraging result, in<br />

fact it plays a role analogous to the breeder reactor’s properties we had seen at work in the<br />

Drosophila/genetics interaction. The “complexity” of the insect lay in its ability to produce<br />

an ever increasing number of mutations when interacting with the experimental methods of<br />

the geneticists. These mutations, by challenging the scientists’ tools, were forcing them to<br />

refine their theories to keep up with the insect’s capacities. Similarly, chess’s “ability” to<br />

turn out ever new forms of combinatorial explosions under the scientists’ pressure to keep<br />

it under control forces them to devise more and more refined methods (read, “theories”) to<br />

keep up with the game’s “complexity.” In both cases, the productive relationship can be es-<br />

tablished because there is a conceptual framework that makes the object’s complexity<br />

thinkable and that allows the search for a solution to start. In genetics’ case, this was the<br />

theory of the gene, in Artificial Intelligence is the conception of a game as a search-space,<br />

e.g. as a space of single, static positions generated recursively by the application of the rules<br />

of the game.<br />

The framework provided by Shannon shifts all the emphasis in the study of chess from<br />

“solving the game,” to “searching the space for an acceptable solution.” The problem of Ar-<br />

tificial Intelligence becomes how to search that space for a solution as good as a human be-<br />

ing could find, providing thus, in a single stroke, a theory of thinking and a theory of chess.<br />

It is the solution of this problem that attracts the attention of Herbert Simon and Allen New-<br />

ell.<br />

Around 1950, Herbert Simon was a young economist working in the “backwaters”<br />

area of industrial organizations and had already published a substantial work, Administra-

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