Arthur Samuel’s checker-playing program,
described in that collection but written in the
1950s, was a tour-de-force given both the limi-tations of the IBM 704 hardware for which the
program was written as a checkout test and the
limitations of the assembly language in which it
was written. Checker playing requires modest
intelligence to understand and considerable intelligence
to master. Samuel’s program (since
outperformed by the Chinook program) is all
the more impressive because the program
learned through experience to improve its own
checker-playing ability—from playing human
opponents and playing against other computers.
Whenever we try to identify what lies at the
core of intelligence, learning is sure to be mentioned
(see, for example, Marvin Minsky’s 1961
paper “Steps Toward Artificial Intelligence.”)