Best Quotes from The Sciences Of The Artificial by Herbert A. Simon with Page Numbers

The central task of a natural science is to make the wonderful commonplace: to show that complexity, correctly viewed, is only a mask for simplicity.

This is the task of natural science: to show that the wonderful is not incomprehensible, to show how it can be comprehended but not to destroy wonder.

The aesthetics of natural science and mathematics is at one with the aesthetics of music and painting; both inhere in the discovery of a partially concealed pattern.

The world we live in today is much more a man-made, or artificial, world than it is a natural world.

Artificial things are not apart from nature. They are what they are in order to satisfy our desire to fly or to eat well.

A science of the artificial will be closely akin to a science of engineering but very different.

Fulfillment of purpose or adaptation to a goal involves a relation among three terms: the purpose or goal, the character of the artifact, and the environment in which the artifact performs.

If wishes were horses, all beggars would ride.

Whether a knife will cut depends on the material of its blade and the hardness of the substance to which it is applied.

Description of an artifice in terms of its organization and functioning - its interface between inner and outer environments - is a major objective of invention and design activity.

Because scarcity is a central fact of life... it is a task of rationality to allocate scarce things.

Economics exhibits in purest form the artificial component in human behavior.

The outer environment is defined by the behavior of other individuals, firms, markets, or economies.

In contrast to a situation where the adaptation process is itself problematic, we can predict the system's behavior without knowing how it actually computes the optimal output.

The question of maximizing the difference between revenue and cost becomes interesting when, in more realistic circumstances, we ask how the firm actually goes about discovering that maximizing quantity.

Real-world optimization, with or without computers, is impossible; the real economic actor is in fact a satisficer.

What a person cannot do he or she will not do, no matter how strong the urge to do it.

Markets appear to conserve information and calculation by assigning decisions to actors who can make them on the basis of information that is available to them locally.

The most significant fact about this system is the economy of knowledge with which it operates, or how little the individual participants need to know in order to be able to take the right action.

The evolution of firms and of economies does not lead to any easily predictable equilibrium, much less an optimum.

The apparent complexity of our behavior over time is largely a reflection of the complexity of the environment in which we find ourselves.

Human beings, viewed as behaving systems, are quite simple.

A thinking human being is an adaptive system; men's goals define the interface between their inner and outer environments.

Psychology as a science should illuminate the artificial structures and processes underlying human cognition.

The artificiality—hence, variability—of human behavior hardly calls for evidence beyond our observation of everyday life.

Only human pride argues that the apparent intricacies of our path stem from a quite different source than the intricacy of the ant's path.

To the extent that they are effectively adaptive, their behavior will reflect characteristics largely of the outer environment.

Only a gross knowledge of the characteristics of the human information-processing system is needed to predict behavior.

The truth or falsity of the hypothesis should be independent of whether ants, viewed more microscopically, are simple or complex systems.

What we learn about how individuals think and solve problems should inform our understanding of the inherent simplicity behind human cognition.

More memory does not necessarily mean more complexity.

Understanding systems, especially systems capable of understanding problems in new task domains, are learning systems.

Meaningful material is indexed in such a way that it can be accessed readily when it is relevant.

Learning is any change in a system that produces a more or less permanent change in its capacity for adapting to its environment.

The adaptiveness of the human organism makes it an elusive and fascinating target of our scientific inquiries.

The apparent complexity of our behavior over time is largely a reflection of the complexity of the environment in which we find ourselves.

The inner environment, the hardware, is simple. Complexity emerges from the richness of the outer environment.

Exercise for the reader: write a computer program that... will choose a reasonable path to deliver a passenger from one point to another.

Intuition is a genuine enough phenomenon which can be explained rather simply: most intuitive leaps are acts of recognition.

Nothing that we have discovered about memory requires us to revise our basic verdict about the complexity or simplicity of human cognition.

Everyone designs who devises courses of action aimed at changing existing situations into preferred ones.

Design, so construed, is the core of all professional training; it is the principal mark that distinguishes the professions from the sciences.

The proper study of those who are concerned with the artificial is the way in which that adaptation of means to environments is brought about.

The professional schools can reassume their professional responsibilities just to the degree that they discover and teach a science of design.

What is called for is not a departure from the fundamental but an inclusion in the curriculum of the fundamental in engineering along with the fundamental in natural science.

The damage to professional competence caused by the loss of design from professional curricula gradually gained recognition in engineering and medicine.

A science of artificial phenomena is always in imminent danger of dissolving and vanishing.

The logic of optimization methods can be sketched as follows: The 'inner environment' of the design problem is represented by a set of given alternatives of action.

Finding satisfactory actions is a realistic approach when optimization is computationally infeasible.

The design process involves management of the resources of the designer, so that his efforts will not be dissipated unnecessarily in following lines of inquiry that prove fruitless.

We are energized by the great power our technological knowledge bestows on us.

Most of the framers of the Constitution accepted very restricted objectives for their artifact principally the preservation of freedom in an orderly society.

The organization of ECA...provided a common problem representation within which all could work.

The task is not to design without data but to incorporate assessments of the quality of the data, or its lack of quality, in the design process itself.

Each of these representations had some basis in the congressional legislation establishing the ECA.

It is probably the strictest standard we can generally satisfy with real-world problems of this complexity.

The aim here is to enable them not just to evaluate alternatives better but especially to experience the world in more and richer ways.

Designing without fixed goals has much in common with the processes of biological evolution.

Our essential task a big enough one to be sure is simply to keep open the options for the future or perhaps even to broaden them a bit.

By combinatorics on a few primitive elements, unbounded variety can be created.

"The whole transcends the sum of the parts."

"Natural objects as wholes... are not entirely resolvable into parts; they are more than the sums of their parts."

"Emergence simply means that the parts of a complex system have mutual relations that do not exist for the parts in isolation."

"Holism can be given weaker or stronger interpretations."

"We can learn something about the (relative) gravitational accelerations of binary stars, but not of isolated stars."

"In a pragmatic way, we can build nearly independent theories for each successive level of complexity."

"All complex systems have a structure that can be dissected to find principles that govern their behavior."

"The ominous term 'chaotic' should not be read as 'unmanageable.'"

"Although the future is not predictable in any detail, it is manageable as an aggregate phenomenon."

"Complexity is more and more acknowledged to be a key characteristic of the world we live in."

The whole is more than the sum of the parts in the weak but important pragmatic sense that, given the properties of the parts and the laws of their interaction, it is not a trivial matter to infer the properties of the whole.

Complexity frequently takes the form of hierarchy and that hierarchic systems have some common properties independent of their specific content.

Hierarchy is one of the central structural schemes that the architect of complexity uses.

The time required for the evolution of a complex form from simple elements depends critically on the numbers and distribution of potential intermediate stable forms.

The potential for rapid evolution exists in any complex system that consists of a set of stable subsystems, each operating nearly independently.

If there exists a hierarchy of potential stable subassemblies... then the time required for a subassembly can be expected to be about the same at each level.

One of the interesting characteristics of nerve cells and telephone wires is that they permit very specific strong interactions at great distances.

In problem solving, a partial result that represents recognizable progress toward the goal plays the role of stable subassembly.

The task of science is to make use of the world's redundancy to describe that world simply.

The notion of substituting a process description for a state description of nature has played a central role in the development of modern science.