The Sciences of the Artificial

No sharp line divides learning things that are already known to others from learning things that are new to the world.

Not only are such systems capable of discovering new concepts but also they can plan sequences of experiments, postulate reaction paths for complex chemical reactions, induce rules for interpreting data from mass spectrogram analysis, and enlarge the state space of a system to accommodate variables that are not directly observable.

Designing is a kind of mental window shopping. Purchases do not have to be made to get pleasure from it.

If asked to read a string of digits or letters and simply to repeat them back, a subject can generally perform correctly on strings up to seven or even ten items in length. If almost any other task, however simple, is interposed between the subject’s hearing the items and repeating them, the number retained drops to two.

There is no reason to expect that the decomposition of the complete design into functional components will be unique.

The success of planning on such a scale may call for modesty and restraint in setting the design objectives

Hence all mathematical derivation can be viewed simply as change in representation,

It is quite easy to devise systems in which each subsystem is optimally adapted to the other subsystems around it, but in which the

The thesis is that certain phenomena are “artificial” in a very specific sense: they are as they are only because of a system’s being molded, by goals or purposes, to the environment in which it lives. If natural phenomena have an air of “necessity” about them in their subservience to natural law, artificial phenomena have an air of “contingency” i