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A mathematical model/computer simulation of adaptive system interaction
Author(s) -
Muir Donal E.
Publication year - 1986
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830310104
Subject(s) - computer science , range (aeronautics) , futures studies , management science , complex adaptive system , normative , adaptive behavior , mathematical model , artificial intelligence , human–computer interaction , psychology , social psychology , philosophy , materials science , physics , epistemology , quantum mechanics , economics , composite material
An idealized mathematical model of adaptive‐system behavior, using conventional economic decision‐theory assumptions, is stated. The data‐processing capacity of this model is analyzed, revealing that it would be rapidly overwhelmed by even moderate complexity. To circumvent this difficulty, a practical algorithmic approximation is developed. This, in turn, is tested by basing computer simulations of both single adaptive systems and small‐group interactional systems upon it. Simulants respond to conditioning, are able to master complex sequences of decisions, are able to put ideas together to synthesize solutions to problems, interact with other simulants in a way that tends to produce interactional patterns (mini‐cultures) which serve their survival, and perform in a manner deemed realistic by a wide range of simulation participants. It is thus concluded that the underlying mathematical model of adaptive‐system behavior is supported as a valid paradigm for further theoretical research and instruction in the economics of adaptive‐system decision making Participant interest in the simulations themselves–as evidenced by requests to participate again–and resulting measurable gains in insight into the economics of interaction–as evidenced by rapidly increasing ability to both anticipate and control the behavior of simulated others–indicate that they, too, could serve as research and instructional tools. Theoretical research applications could range from explorations of the consequences of memory size, risk taking, or analytical foresight upon the performance of individual adaptive systems, to investigations of the effects of changes in size, interactional patterns, normative or enforcement systems for social systems (such as families, friends, classrooms, work groups, military units, and so forth). Instructional applications could include practicums in decision theory and conditioning in academic settings such as economics, sociology, and psychology, and in a wide variety of applied settings such as counseling, therapy, rehabilitation, teaching, training, management, and marketing. Applied research efforts might investigate the effectiveness of simulation as a means of measuring or enhancing such skills as leadership, teaching, training, or adaptability, as discussed above.