EMERGENT VALUE ORIENTATION IN SELF-ORGANIZATION OF AN ANIMAT

The genetic algorithms proposed by Holland [Holland, J.H., 1992/1975. Adaptation in Natural and Artificial Systems. MIT Press Cambridge] hav e previously been used in computer experiments to study knowledge grow th in simple artificial animal models ('animats') acting in a simulate d environment. In the present paper, this work is extended to include the concepts of orientation theory [Bossel, H., 1977. Orientors of non routine behavior. In: H. Bossel (Editor), Concepts and Tools of Comput er-Assisted Policy Analysis. Birkhauser Verlag, Basel, pp. 227-265]. O rienters are value orientations emerging in the evolutionary adaptatio n of systems to their specific environments. The animat experiments de monstrate how knowledge growth during the learning phase leads to bala nced attention to basic needs, i.e. satisfaction of basic orientors (e ffectiveness, freedom of action, security, adaptability in addition to existence and coexistence needs) with some variation of emphasis amon g individuals in a population. The results of the computer experiments suggest that (multidimensional) value orientation is a basic emergent feature of evolutionary adaptation to environments characterized by s parse resources, variety, fluctuation, and change. Pathological behavi or and system failure must be expected if there is insufficient attent ion to any of the basic orientors. Apart from these basic insights, th e approach employed here can be applied more generally to comprehensiv e assessments of system fitness and performance, and in particular to comparative studies of the feasibility and viability of future develop ment paths. (C) 1997 Elsevier Science B.V.