Complex adaptive system

About: Complex adaptive system is a research topic. Over the lifetime, 3190 publications have been published within this topic receiving 111947 citations. The topic is also known as: Complex adaptive system, CAS.

From bouncing back, to nurturing emergence: reframing the concept of resilience in health systems strengthening.

Abstract: Recent health system shocks such as the Ebola disease outbreak have focused global health attention on the notion of resilient health systems. In this commentary, we reflect on the current framing of the concept of resilience in health systems discourse and propose a reframing. Specifically, we propose that: (1) in addition to sudden shocks, health systems face the ongoing strain of multiple factors. Health systems need the capacity to continue to deliver services of good quality and respond effectively to wider health challenges. We call this capacity everyday resilience; (2) health system resilience entails more than bouncing back from shock. In complex adaptive systems (CAS), resilience emerges from a combination of absorptive, adaptive and transformative strategies; (3) nurturing the resilience of health systems requires understanding health systems as comprising not only hardware elements (such as finances and infrastructure), but also software elements (such as leadership capacity, power relations, values and appropriate organizational culture). We also reflect on current criticisms of the concept of resilient health systems, such as that it assumes that systems are apolitical, ignoring actor agency, promoting inaction, and requiring that we accept and embrace vulnerability, rather than strive for stronger and more responsive systems. We observe that these criticisms are warranted to the extent that they refer to notions of resilience that are mismatched with the reality of health systems as CAS. We argue that the observed weaknesses of resilience thinking can be addressed by reframing and applying a resilience lens that is better suited to the attributes of health systems as CAS.

Complexity Theory and Strategic Change: an Empirically Informed Critique*

Abstract: We present a four-year ethnographic study of a public-sector organization and use narrative to describe its development in terms of four complexity theory concepts: sensitivity to initial conditions, negative and positive feedback processes, disequilibrium and emergent order. Our study indicates that order emerges at the boundary between the organization's legitimate and shadow systems. We suggest that the underlying dynamic leading to the emergent order is the need to reduce anxiety. Our findings cause us to question the assertion that organizations are naturally complex adaptive systems producing novel forms of order. We propose an alternate view that in social systems, equilibrium-seeking behaviour is the norm; such systems can self-organize into hierarchy. We draw attention to some of the difficulties we found in applying complexity-theory concepts to a social system and conclude by advocating the development of complexity theory through the incorporation of insights from psychology and social theory.

Nonlinear pedagogy: a constraints-led framework for understanding emergence of game play and movement skills.

Abstract: Team sport competition can be characterized as a complex adaptive system in which concepts from nonlinear dynamics can provide a sound theoretical framework to understand emergent behavior such as movement coordination and decision making in game play. Nonlinear Pedagogy is presented as a methodology for games teaching, capturing how phenomena such as movement variability, self-organization, emergent decision making, and symmetry-breaking occur as a consequence of interactions between agent-agent and agent-environment constraints. Empirical data from studies of basketball free-throw shooting and dribbling are used as task vehicles to exemplify how nonlinear phenomena characterize game play in sport. In this paper we survey the implications of these data for Nonlinear Pedagogy, focusing particularly on the manipulation of constraints in team game settings. The data and theoretical modeling presented in this paper provide a rationale in nonlinear dynamics for the efficacy of a prominent model of game play teaching, Teaching Games for Understanding approach.

Social Insect Colonies as Complex Adaptive Systems

Abstract: Social insect societies are complex adaptive systems that self-organize within a set of constraints. Although it is important to acknowledge that global order in social insects can arise as a result of internal interactions among insects, it is equally important to include external factors and constraints in the picture, especially as the colony and its environment may influence each other through interactions among internal and external factors. The scope of this remark goes beyond social insects and applies to a wide range of biological systems, including ecosystems.

The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI

Abstract: In The Allure of Machinic Life, John Johnston examines new forms of nascent life that emerge through technical interactions within human-constructed environments--"machinic life"--in the sciences of cybernetics, artificial life, and artificial intelligence. With the development of such research initiatives as the evolution of digital organisms, computer immune systems, artificial protocells, evolutionary robotics, and swarm systems, Johnston argues, machinic life has achieved a complexity and autonomy worthy of study in its own right. Drawing on the publications of scientists as well as a range of work in contemporary philosophy and cultural theory, but always with the primary focus on the "objects at hand"--the machines, programs, and processes that constitute machinic life--Johnston shows how they come about, how they operate, and how they are already changing. This understanding is a necessary first step, he further argues, that must precede speculation about the meaning and cultural implications of these new forms of life. Developing the concept of the "computational assemblage" (a machine and its associated discourse) as a framework to identify both resemblances and differences in form and function, Johnston offers a conceptual history of each of the three sciences. He considers the new theory of machines proposed by cybernetics from several perspectives, including Lacanian psychoanalysis and "machinic philosophy." He examines the history of the new science of artificial life and its relation to theories of evolution, emergence, and complex adaptive systems (as illustrated by a series of experiments carried out on various software platforms). He describes the history of artificial intelligence as a series of unfolding conceptual conflicts--decodings and recodings--leading to a "new AI" that is strongly influenced by artificial life. Finally, in examining the role played by neuroscience in several contemporary research initiatives, he shows how further success in the building of intelligent machines will most likely result from progress in our understanding of how the human brain actually works.