Herbert Simon

Nuggets from "The Sciences of the Artificial", 2nd ed. by the Nobel laureate from Carnegie Mellon University - Professor Herbert Simon. (3rd edition ISBN: 0262691914) Published by The MIT Press, Cambridge, MA, 1981.

Selected by Nikunj Mehta

This book is a must read for any engineer, sociologist, writer and urban planner. Simon shows how such diverse fields have a common thread and that all these fields are based on the science of the "Artificial". They are all concerned with how things ought to be rather than how they are. It provides a fresh perspective on flexible and growing systems by considering a system to be a self adapting organism just like a warm blooded animal that can maintain its temperature by employing prediction, insulation and feedback.
 * Essence of design:: Engineering, medicine, business, architecture and painting are concerned not with the necessary but with the contingent - not with how things are but with how they might be - in short, with design.


 * Essence of science:: The central task of a natural science is to make the wonderful commonplace.


 * Normative or descriptive:: The engineer, and more generally the designer, is concerned with how things ought to be - how they ought to be in order to attain goals, and to function … With goals and "oughts" we also introduce into the picture the dichotomy between normative and descriptive. Natural science has found a way to exclude the normative and to concern itself solely with how things are … Artificial things can be characterized in terms of functions, goals and adaptation.


 * Characteristics of artifacts:: 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.


 * Artifact as an "Interface":: An artifact can be thought of as a meeting point - an interface… - between an "inner" environment, the substance and organization of the artifact itself, and an "outer" environment, the surroundings in which it operates.


 * Environment:: ... advantage of dividing outer from inner environment in studying an adaptive or artificial system is that we can often predict behavior from knowledge of the system's goals and its outer environment, with only minimal assumptions about the inner environment. … In one way or another the designer insulates the inner system from the environment, so that an invariant relation is maintained between inner system and goal, independent of variations over a wide range in most parameters that characterize the outer environment.


 * Homeostasis:: Quasi independence from the outer environment may be maintained by various forms of passive insulation, by reactive negative feedback, by predictive adaptation, or by various combinations of these.


 * Determining behavior:: The outer environment determines the conditions for goal attainment - if the system is properly designed, it will be adapted to the outer environment, so that its behavior will be determined in large part by the behavior of the latter...


 * Simulation:: ... it is typical of many kinds of design problems that the inner system consists of components whose fundamental laws of behavior … are well known. The difficulty of the design problem often resides in predicting how an assemblage of such components will behave.


 * Top-down decomposition:: We do not have to know … all the internal structure of the system but only that part of it that is crucial to the abstraction. ... if it were not, the top down strategy that built the natural sciences ... would have been infeasible. We knew a great deal about the gross physical and chemical behavior of matter before we had an atomic theory, and a great deal about atoms before we had any theory of elementary particles…


 * Microtheories::... the possibility of building a mathematical theory of a system does not depend on having an adequate microtheory of the natural laws that govern the system components. Such a microtheory might indeed be simply irrelevant.


 * Complexity a fa&ccedil;ade:: As we succeed in broadening and deepening our knowledge - theoretical and empirical - about computers, we shall discover that in large part their behavior is governed by simple general laws, that what appeared as complexity in the computer program was to a considerable extent complexity of the environment to which the program was seeking to adapt its behavior.


 * Optimize or satisfice:: The decision maker has a choice between optimal decisions for an imaginary simplified world or decisions that are "good enough," that satisfice, for a world approximating the complex real one more closely.


 * Internal limitations:: What a person cannot do he will not do, no matter how much he wants to do it. Normative economics has shown that exact solutions to the larger optimization problems of the real world are simply not within reach or sight. ... the behavior of an artificial system may be strongly influenced by the limits of its adaptive capacities.


 * Adaptation:: ... to use feedback to correct for unexpected or incorrectly predicted events. Even if the anticipation of events is imperfect and the response to them less than accurate, adaptive systems may remain stable in the face of sizable jolts…


 * Evolution:: The simplest scheme of evolution is one that depends on two processes; a generator and a test. The task of the generator is to produce variety, new forms that have not existed previously, whereas the task of the test is to cull out the newly generated forms so that only those that are well fitted to the environment will survive.


 * Hierarchy and the functional paradigm:: To design ... a complex structure, one powerful technique is to discover viable ways of decomposing it into semi-independent components corresponding to its many functional parts. The design of each component can then be carried out with some degree of independence of the design of others, since each will affect the others largely through its function and independently of the details of the mechanisms that accomplish the function.


 * Process determines style:: ... both the shape of the design and the shape and organization of the design process are essential components of a theory of design.


 * Taxonomy of representation:: An early step toward understanding any set of phenomena is to learn what kinds of things there are in the set - to develop a taxonomy.


 * Design of complex, durable systems:: ... the characteristics and complexities of designing artifacts on a societal scale The success of planning on such a scale may call for modesty and restraint in setting the design objectives and drastic simplification of the real-world situation in representing it for purposes of the design process.


 * Human cognition architecture:: Human memory is best regarded as an extension ... of the environment in which human thought processes take place and not as an increment in the complexity of these processes. What is remarkable about the whole architecture is ... that memory enables the system to operate efficiently in a wide array of different task domains using the same basic equipment that it employs to understand and solve Tea Ceremony problems or simple statics problems in physics.


 * Complexity as hierarchy:: ... 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.


 * Evolution of complex systems:: 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.


 * Near decomposability:: ... hierarchies have the property of near decomposability. Intracomponent linkages are generally stronger than intercomponent linkages. This fact has the effect of separating the high-frequency dynamics of a hierarchy - involving the internal structure of the components - from the low-frequency dynamics - involving interaction among components.


 * Description of complex systems:: ... two main types of description ... (for) understanding of complex systems ... (are) state description and process description. The former characterizes the world as senses; they provide the criteria for identifying objects, often by modeling the objects themselves. The latter characterize the world as acted upon; they provide the means for producing or generating objects having the desired characteristics.

August 3 1999.