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.

A Conceptual Model of Systems Thinking Leadership in Community Colleges

Abstract: The pluralistic and often competing goals of myriad constituents, the changing demographics of students, the uncertainty of funding, and the growing demands for accountability from stakeholders have increased the complexity of systems which community college leaders must manage. Emerging from the recent literature on community colleges is a call for new models of leadership in the context of leading in an increasingly uncertain and complex environment. Systems thinking offers a means to help leaders respond to these growing organizational complexities and move leadership from a traditional bureaucratic model to a more adaptive model. A systematic review of literature on systems thinking’s application to organizational performance in higher education was bolstered with evidence from healthcare. Findings revealed three reoccurring ways in which leaders apply systems thinking processes for improving organizational performance. A conceptual model for systems thinking leadership is proposed in which the three processes, characterized as discovery, framing, and action, can be enacted either individually or sequentially for enhancing organizational performance. The model draws upon boundary critique, critical systems thinking, systemic intervention, total systems intervention, systems dynamics, soft systems methodology, complexity theory and complex adaptive systems, yet uses language more readily identifiable to community college practitioners.

Smart City 5.0 as an Urban Ecosystem of Smart Services

Abstract: In this paper, Smart City is described as a live and constantly developing complex adaptive system operating in an uncertain environment with many participants and actors involved. The vision of the “Smart City 5.0” concept as an ecosystem of smart services based on multi-agent technology is presented. It is characterized by the cooperation of Artificial Intelligence systems and humans, and can harmoniously balance all spheres of life and contradictory interests of different city actors. In this concept, each smart service is presented by an autonomous agent. They can compete or cooperate with each other through a service bus and interact both vertically and horizontally on the basis of specialized protocols. Top-level services can be constructed as autonomous multi-agent systems of a lower level, where an agent can recursively reveal a new service for itself. The paper describes the design principals and the general architecture of the digital platform including the basic agent of smart service, the architecture and basic principles of smart city ontologies and knowledge base. The paper shows how the platform can support the decision-making life cycle for managing any urban object and the adaptive behaviour of Smart City 5.0 is compared with the fixed scenarios Smart City 4.0.

Complexity systems management method

Abstract: The Complexity Systems Management (CSM) Method is a scientifically derived business process method for managing complex events and situations. The CSM Method™ is based on new scientific evidence that explains the behaviors of complex adaptive systems. This same scientific evidence gives rise to a new method of science, known as a priori optionality. A priori optionality is based on six scientifically derived tenets that are systematically applied using the CSM Method™ to more accurately characterize the behaviors of complex adaptive systems and manage complex events and situations. Applications of the CSM Method are integrally tied to specialized knowledgebases and a plurality of automated software applications.

Evolution of Brain and Language.

Abstract: The evolution of language and the evolution of the brain are tightly interlinked. Language evolution represents a special kind of adaptation, in part because language is a complex behavior (as opposed to a physical feature) but also because changes are adaptive only to the extent that they increase either one's understanding of others, or one's understanding to others. Evolutionary changes in the human brain that are thought to be relevant to language are reviewed. The extent to which these changes are a cause or consequence of language evolution is a good question, but it is argued that the process may best be viewed as a complex adaptive system, in which cultural learning interacts with biology iteratively over time to produce language.

Empiricism in ecological economics: a perspective from complex systems theory

Abstract: Economies are open complex adaptive systems far from thermodynamic equilibrium, and neo-classical environmental economics seems not to be the best way to describe the behaviour of such systems. Standard econometric analysis (i.e. time series) takes a deterministic and predictive approach, which encourages the search for predictive policy to ‘correct’ environmental problems. Rather, it seems that, because of the characteristics of economic systems, an ex-post analysis is more appropriate, which describes the emergence of such systems’ properties, and which sees policy as a social steering mechanism. With this background, some of the recent empirical work published in the field of ecological economics that follows the approach defended here is presented. Finally, the conclusion is reached that a predictive use of econometrics (i.e. time series analysis) in ecological economics should be limited to cases in which uncertainty decreases, which is not the normal situation when analysing the evolution of economic systems. However, that does not mean we should not use empirical analysis. On the contrary, this is to be encouraged, but from a structural and ex-post point of view.