p.3 We are now poised for a great advance that will bring the digital computer and the
tools of mathematics and the behavioral sciences to bear on the very core of managerial activity - on the exercise
of judgment and intuition; on the processes of making complex decisions.
p.4-5 A problem is well structured to the extent that it satisfies the following criteria:
1. It can be described in terms of numerical variables, scalar and vector quantities.
2. The goals to be attained can be specified in terms of a well-defined objective function - for example,
the maximization of profit or the minimization of cost.
3. There exist computational routines (algorithms) that permit the solution to be found and stated in actual
mathematical terms.
p.6 Even while operations research is solving well-structured problems, fundamental research is
dissolving the mystery of how humans solve ill-structured problems. Moreover, we have begun to learn how to use computers
to solve these problems, where we do not have systematic and efficient computational algorithms. And we now know,
at least in a limited area, not only how to program computers to perform such problem-solving activities successfully; we
know also how to program computers to learn to do these things.
In short, we now have the elements of a
theory of heuristic (as contrasted with algorithmic) problem solving; and we can use this theory both to understand human
heuristic processes and to simulate such processes with digital computers. Intuition, insight, and learning are no
longer exclusive possessions of humans: any large high-speed computer can be programmed to exhibit them also.
p.7 Let me summarize as concretely as possible my assessment of the present and future state of the art
and theory of heuristic problem solving. As of the present-1957:
1. Digital computers can perform certain heuristic problem-solving tasks for which no algorithms are available.
2.
In doing so, they use processes that are closely parallel to human problem-solving processes.
3. Within limits, these machines
learn to improve their performance on the basis of experience (not merely by memorizing specific patterns of successful behavior,
but by reprogramming themselves in ways that parallel at least some human learning procedures).
On the basis of these developments, and with the speed with which research is this field is progressing,
I am willing to make the following predictions, to be realized within the next ten years:
1. That within ten years a digital computer will be the world's chess champion, unless the
rules bar it from competition.
