Showing papers on "Complex adaptive system published in 1995"

The science of complexity: An alternative perspective for strategic change processes

Abstract: The two perspectives of strategy process most firmly established in the literature—strategic choice and ecology—assume the same about system dynamics: negative feedback processes driving successful systems (individual organizations or populations of organizations) toward predictable equilibrium states of adaptation to the environment. This paper proposes a third perspective, that of complex adaptive systems. The framework is provided by the modern science of complexity: the study of nonlinear and network feedback systems, incorporating theories of chaos, artificial life, self-organization and emergent order. Here system dynamics are characterized by positive and negative feedback as systems coevolve far from equilibrium, in a self-organizing manner, toward unpredictable long-term outcomes.

How Economists Can Get Alife

Abstract: This paper presents a summary overview of the fast-developing field of "artificial life," stressing aspects that seem especially relevant for the study of decentralized market economies. In particular, recent artificial life work combining evolutionary game theory with preferential partner selection is described in some detail. This work is currently being applied to the endogenous formation and evolution of trade networks.

Adaptation and the Modular Design of Organisms

Abstract: In this paper the implications of the theory of evolutionary computation for evolutionary biology are explored. It is claimed that the concept of “representations” is particularly useful to understand the evolution of complex adaptation and the origin of the modular design of higher organisms. Modularity improves the adaptability of complex adaptive systems, but arises most likely as a side effect of adaptive evolution rather than being an adaptation itself.

Three Illustrations of Artificial Life's Working Hypothesis

Abstract: Artificial life uses computer models to study the essential nature of the characteristic processes of complex adaptive systems proceses such as self-organization, adaptation, and evolution. Work in the field is guided by the working hypothesis that simple computer models can capture the essential nature of these processes. This hypothesis is illustrated by recent results with a simple population of computational agents whose sensorimotor functionality undergo open-ended adaptive evolution. These might illuminate three aspects of complex adaptive systems in general: punctuated equilibrium dynamics of diversity, a transition separating genetic order and disorder, and a law of adaptive evolutionary activity.

The Logical Structure of the Cognitive Mechanisms Guiding Psychological Development

Abstract: my supervisor, Professor Brian Josephson, for giving m e t he o pportunity t o w ork under his guidance and for helping m e m aster the transition from course-work to research work. I h ave learned a great d eal in countless discussions with Brian, but also from several members of the Theory of Condensed Matter Group. Above all I wish to thank my family for their constant encouragement and support both d uring t he application process and during m y s t ay in Cambridge.

Social Complex Adaptive Systems: Some Hawaiian Examples

Abstract: The theory of Complex Adaptive Systems, developed within the last decade, is applied to the evolution of the ancient Hawaiian polities. A Complex Adaptive System (CAS) consists of numerous independent parts or "agents" undergoing constant nonlinear interactions. The complexity of a CAS emerges heterarchically from the interactions of agents following simple local rules. The evolution of a socio-cultural CAS such as a Hawaiian polity is generated by the interaction of hierarchy and heterarchy; nonlinear change and ordered stability; and self organization, adaptation, and chance.

How to Get Alife

Abstract: This essay discusses the potential relevance of artificial life research for the study of economic processes.

The Cognitive Mechanisms Guiding Psychological Development

Abstract: This Thesis presents a model of cognitive development inspired by Piaget's "Genetic Epistemology". It is observed that the epigenetic process described by Piaget posess mechanisms and behaviour that characterise complex adaptive systems. A model of bipedal motion based around the "Bucket Brigade" algorithm of Holland is presened to explore this relationship.

Constraints on Task and Search Complexity in GA + NN Models of Learning and Adaptive Behaviour

Abstract: Models of adaptive behaviour are normally highly complex due to a greater emphasis on, learning by interaction with the environment, flexible behaviour, and, an evolutionary learning methodology. This research investigates how a combination of Genetic Algorithms and Neural Networks (GA+NN) can be used to model behaviour to solve a task requiring co-operation between two artificial autonomous agents. In particular, the results illustrate how a complex learning task (that is, a simple game of football which requires a highly dynamic interaction between agents and the environment) is learned more efficiently as a result of GA operator modifications and modularisation of the learning task. The overall effect of these changes is to constrain the search space that the hybrid GA+NN system can potentially explore. A distinction between task and search complexity provides a useful framework for a clearer comprehension of the nature of constraints vis-a-vis the modelling process (generally characterised as a complex adaptive system). Broad implications of the findings on modular models of adaptive behaviour and the role of constraints on complexity are briefly discussed.