Two Meanings of Complex Adaptive Systems

Adaptive Systems ◽

Social Insect ◽

Functional Organization ◽

General Rule ◽

Insect Colonies ◽

Complex Adaptive ◽

Selection For

In complex systems theory, two meanings of a complex adaptive system (CAS) need to be distinguished. The first, CAS1, refers to a complex system that is adaptive as a system; the second, CAS2, refers to a complex system of agents which follow adaptive strategies. Examples of CAS1 include the brain, the immune system, and social insect colonies. Examples of CAS2 include multispecies ecosystems and the biosphere. This chapter uses multilevel selection theory to clarify the relationships between CAS1 and CAS2. The general rule is that for a complex system to qualify as CAS1, selection must occur at the level of the complex system (e.g., individual-level selection for brains and the immune system, colony-level selection for social insect colonies). Selection below the level of the system tends to undermine system-level functional organization. This general rule applies to human social systems as well as biological systems and has profound consequences for economics and public policy.

Social Insect Colonies as Complex Adaptive Systems

Ecosystems ◽

10.1007/s100219900038 ◽

1998 ◽

Vol 1 (5) ◽

pp. 437-443 ◽

Cited By ~ 72

Author(s):

Eric Bonabeau

Keyword(s):

Adaptive Systems ◽

Social Insect ◽

Insect Colonies ◽

Mathematics as Complex System: Learning in Complex Adaptive Systems

Complicity An International Journal of Complexity and Education ◽

10.29173/cmplct8841 ◽

2010 ◽

Vol 7 (1) ◽

Cited By ~ 2

Author(s):

Michelle E. Jordan

Keyword(s):

Complex System ◽

Adaptive Systems ◽

A Response to Elizabeth Mowat & Brent Davis

Why religion is better conceived as a complex system than a norm-enforcing institution

Behavioral and Brain Sciences ◽

10.1017/s0140525x13003038 ◽

2014 ◽

Vol 37 (3) ◽

pp. 275-276 ◽

Cited By ~ 2

Author(s):

Richard Sosis ◽

Jordan Kiper

Keyword(s):

Complex System ◽

Cultural Evolution ◽

Adaptive Systems ◽

Systems Approach ◽

Group Level ◽

AbstractAlthough religions, as Smaldino demonstrates, provide informative examples of culturally evolved group-level traits, they are more accurately analyzed as complex adaptive systems than as norm-enforcing institutions. An adaptive systems approach to religion not only avoids various shortcomings of institutional approaches, but also offers additional explanatory advantages regarding the cultural evolution of group-level traits that emerge from religion.

The complexity of the corporation

Human Systems Management ◽

10.3233/hsm-2004-23202 ◽

2004 ◽

Vol 23 (2) ◽

pp. 71-78

Author(s):

Duncan A. Robertson

Keyword(s):

Complex System ◽

Firm Performance ◽

Adaptive Systems ◽

Management Science ◽

We discuss the notion of complexity as applied to firms and corporations. We introduce the background to complex adaptive systems, and discuss whether this presents an appropriate model or metaphor to be used within management science. We consider whether a corporation should be thought of as a complex system, and conclude that a firm within an industry can be defined as a complex system within a complex system. Whether we can say that the use of complexity research will fundamentally improve firm performance will depend on the effect on success derived from its application.

Beyond root cause analysis: How variation analysis can provide a deeper understanding of causation in complex adaptive systems

Journal of Patient Safety and Risk Management ◽

10.1177/2516043521992908 ◽

2021 ◽

Vol 26 (2) ◽

pp. 74-80

Author(s):

Paul Stretton

Keyword(s):

Complex System ◽

Adaptive Systems ◽

Probabilistic Approach ◽

Root Cause Analysis ◽

Linear Processes ◽

Cause Analysis ◽

Root Cause ◽

Root cause analysis (RCA) is a recognised approach to understanding causation of adverse events across high-risk industries including healthcare. These methodologies were developed during the early part of the twentieth century when the workplace could be understood as a series of linear processes. Within a complex system these approaches offer limited insight, which has since been recognised within healthcare literature. This paper proposes an approach to understanding of causation that addresses Hollnagel’s ‘hypothesis of different causes’ and integrates Safety I and Safety II approaches. This develops Stretton’s Lilypond Model to conceptualise the relationship between work-as-imagined and work-as-done within a complex system where individual adaptations and variations can be analysed. Understanding variation in such a way creates a shift in methodology from a deterministic to a probabilistic approach, which is more appropriate for understanding causation within complex systems.