“The inductive-reasoning system I have described above consists of a multitude of “elements” in the form of belief-models or hypotheses that adapt to the aggregate environment they jointly create. Thus it qualifies as an adaptive complex system. After some initial learning time, the hypotheses or mental models in use are mutually co-adapted. Thus we can think of a consistent set of mental models as a set of hypotheses that work well with each other under some criterion—that have a high degree of mutual adaptedness. Sometimes there is a unique such set, it corresponds to a standard rational expectations equilibrium, and beliefs gravitate into it. More often there is a high, possibly very high, multiplicity of such sets. In this case we might expect inductive reasoning systems in the economy—whether in stock-market speculating, in negotiating, in poker games, in oligopoly pricing, in positioning products in the market—to cycle through or temporarily lock into psychological patterns that may be non-recurrent, path-dependent, and increasingly complicated. The possibilities are rich.”

— W. Brian Arthur

Source: Inductive Reasoning and Bounded Rationality (The El Farol Problem) (1994), p. 8

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W. Brian Arthur 16

American economist 1946

John H. Holland (1929–2015) US university professor

Source: Hidden Order - How Adaptation Builds Complexity (1995), Ch 1. Basic Elements, p. 37

“Reference models can be quite comprehensive, consisting of hundreds or thousands of model objects. This is why various levels of aggregation are used. Reference models provide enterprises with an initial process engineering solution, letting them determine the degree of detail of the model and the business content.”

August-Wilhelm Scheer (1941) German business theorist

Source: ARIS architecture and reference models for business process management (2000), p. 380.

“For the theory-practice iteration to work, the scientist must be, as it were, mentally ambidextrous; fascinated equally on the one hand by possible meanings, theories, and tentative models to be induced from data and the practical reality of the real world, and on the other with the factual implications deducible from tentative theories, models and hypotheses.”

George E. P. Box (1919–2013) British statistician

Source: Science and Statistics (1976), p. 792

“We argue, then, that the sociocultural system is fundamentally of the latter type, and requires for analysis a theoretical model or perspective built on the kinds of characteristics mentioned. In what follows we draw on many of the concepts and principles presented throughout this sourcebook to sketch out aspects of a complex adaptive system model or analytical framework for the sociocultural system.”

Walter F. Buckley (1922–2006) American sociologist

Source: Society as a complex adaptive system (1968), p. 490.

“The second model is the functionalist model of mind. The organism through acquired S-R responses or through operations on the environmental manages to stay alive and adjust itself to the environment. The Thorndykian and Skinnerian approaches to learning and the adaptive model of the psychoanalytical theory come under this heading.”

Thaddus E. Weckowicz (1919–2000) Canadian psychologist

Source: Models of Mental Illness (1984), p. 102

“The effectiveness of any model used to describe and understand behavior of a particular system as a whole ultimately depends on the degree to which that model accurately represents that system. Nevertheless, there have been and are situations in which application of deterministic or animate models to social systems have produced useful results for a short period of time. However, in a longer run, such mismatches usually result in less than desirable results because critical aspects of the social systems were omitted in the less complex model that was used.”

Russell L. Ackoff (1919–2009) Scientist

Ackoff (1999, p. 34) cited in: Michael C. Jackson (2000) Systems Approaches to Management. p. 234.
1990s

“Simulation is the use of models and/or the actual conditions of either the thing being modeled or the environment in which it operates, with the models or conditions in physical, mathematical, or some other form. The purpose of simulation is to explore the various results which might be obtained from the real system by subjecting the model to representative environments which are equivalent to, or in some way representative of, the situations it is desired to understand or investigate. Simulation may involve system hardware and the actual physical environment, or it may involve mathematical models subjected to mathematical forcing or disturbance functions representative of the systems conditions to be studied.”

Harold Chestnut (1917–2001) American engineer

Source: Systems Engineering Tools, (1965), p. 111 as cited in

“Cellular automata are now being used to model varied physical phenomena normally modelled by wave equations, fluid dynamics, Ising models, etc. We hypothesize that there will be found a single cellular automaton rule that models all of microscopic physics; and models it exactly. We call this field DM, for digital mechanics.”

Edward Fredkin (1934) American physicist and computer scientist, a pioneer of digital physics

[An informational process based on reversible universal cellular automata, Physica D: Nonlinear Phenomena, 45, 1–3, September 1990, 254–270, https://www.sciencedirect.com/science/article/pii/016727899090186S, 10.1016/0167-2789(90)90186-S]

“[There is a] basic problem … of building a mathematical model of thought processes, and in particular of those aspects of thought which are concerned with information and decision processes. The perceptron is one type of model -- a set of memory devices connected in random fashion-- which has not yet achieved useful results but certainly seems to be a promising approach. The self-adaptive feedback control system which goes beyond the normal servo function of controlling its output, and in addition controls the parameters by which it controls its output is another which has already achieved pragmatic results in equipment control. It may be that the question of self-adaptation is a key to the whole question of how the human functions in a decisioning situation. For in many cases the ability of the human mind to adapt itself to a changing and complex environment is beyond our present aims in model construction.”

Robert E. Machol (1917–1998) American systems engineer

p ix-x
Information and Decision Processes (1960)

“The problem is not the math itself, but the blind acceptance and even idolatry we have applied to the quantitative models. These predictive models leave citizens befuddled and unable to defend or criticize model-based decisions. We argue that we should accept the fact that we live in a qualitative world when it comes to natural processes. We must rely on qualitative models that predict only direction, trends, or magnitudes of natural phenomena, and accept the possibility of being imprecise or wrong to some degree. We should demand that when models are used, the assumptions and model simplifications are clearly stated. A better method in many cases will be adaptive management, where a flexible approach is used, where we admit there are uncertainties down the road and we watch and adapt as nature rolls on.”

Orrin H. Pilkey (1934) American ecologist

Interview with Orrin Pilkey & Linda Jarvis-Pilkey https://web.archive.org/web/20080105132439/http://www.columbia.edu/cu/cup/publicity/pilkeyinterview.html.
Useless Arithmetic: Why Environmental Scientists Can’t Predict the Future (2007)

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