Studying Complex Adaptive Systems

  title={Studying Complex Adaptive Systems},
  author={John H. Holland},
  journal={Journal of Systems Science and Complexity},
  • J. Holland
  • Published 1 March 2006
  • Computer Science
  • Journal of Systems Science and Complexity
Complex adaptive systems (cas) – systems that involve many components that adapt or learn as they interact – are at the heart of important contemporary problems. The study of cas poses unique challenges: Some of our most powerful mathematical tools, particularly methods involving fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models… 
A molecular approach to complex adaptive systems
This work highlights the current deficit of a theoretical framework for the study of Artificial Chemistries by proposing the Molecular Classifier Systems (MCS.b), a string-based Artificial Chemistry based on Holland's broadcast language to study a subclass of CAS: Cell Signaling Networks (CSNs) which are complex biochemical networks responsible for coordinating cellular activities.
Studying complex adaptive systems using molecular classifier systems
This poster presents a series of experiments focusing on the self-replication ability of the ESIGNET project, a string-based artificial chemistry based on Holland’s Broadcast Language to study a subclass of CAS : Cell Signaling Networks (CSNs) which are complex biochemical networks responsible for coordinating cellular activities.
Critical Analysis of Complex Systems Science and Mechanics
  • Shiyu Qin
  • Computer Science
    Journal of Machine and Computing
  • 2021
This article didactically explain a theoretical and analytic strategy for comprehending and engaging with the complicated processes of the authors' environment rather than giving a complete overview.
Identifying Self-Organization and Adaptability in Complex Adaptive Systems
This paper presents an observation tool, part of a complex adaptive systems modeling framework, that allows for the analysis of these metrics for large-scale complex models and compares and contrast a wide range of metrics implemented in the observation tool.
In this thesis, it is shown, that the analysis of smilingly different CAS coming from different domains, can be performed by following the same recipe.
Atomic switch networks as complex adaptive systems
Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems.
On the Social Implications of Collective Adaptive Systems
This paper shares a discussion that took place between some experts thinking about CAS engineering, focusing on the social implication of CASs and related open research challenges, and hopes that this provides a useful context for future research projects, research grant proposals, and research directions.
A framework and Language for Complex Adaptive System modeling and simulation
An extension to CASL that introduces the concept of ‘semantic grouping’ allows for large scale simulations to execute on relatively modest hardware and an extensible and expandable set of metrics to study key features of CAS such as aggregation, adaptability, and modularity.
Complexity and Self-Organization
This entry introduces some of the main concepts and methods of the science studying complex, self-organizing systems, and networks, in a nontechnical manner, and has obvious applications in information science when studying networks of authors and their publications.
A Framework for Large Scale Complex Adaptive Systems Modeling, Simulation, and Analysis
A language, Complex Adaptive Systems Language (CASL), is proposed, designed for simple creation of CAS models while remaining domain agnostic, and an extension to CASL, called CASL-SG, that introduces the concept of 'semantic grouping' allows for large scale simulations to execute on relatively modest hardware.


Hidden Order: How Adaptation Builds Complexity.
  • J. Koza
  • Computer Science
    Artificial Life
  • 1995
All of these existing systems are computationally expensive and deliver little in the way of important emergent phenomena in relation to the amount of computational effort expended; it may actually preclude emergence of important phenomena that can only materialize in the presence of certain minimum amounts of time or matter.
Perspectives on adaptation in natural and artificial systems
This book consists of 17 papers on the contributions of John Holland by a distinguished group of scholars from a wide range of fields, including the Nobel laureates Kenneth Arrow and Herbert Simon,
Niche Construction: The Neglected Process in Evolution
This book extends evolutionary theory by formally including niche construction and ecological inheritance as additional evolutionary processes, and demonstrates how the theory can resolve long-standing problems in ecology, particularly by advancing the sorely needed synthesis of ecology and evolution.
Learning classifier systems
A gentle introduction to LCSs and their general functionality is provided and the current theoretical understanding of the systems is surveyed, followed by a suite of current successful LCS applications and the most promising areas for future applications and research directions.
Foundations of Learning Classifier Systems
This paper presents an analysis of the population Dynamics of Genetic Algorithms and the Computational Complexity of the XCS Classifier System, and a Mathematical Framework for Studying Learning Classifier Systems.
Theory Of Self Reproducing Automata
Applications of Learning Classifier Systems
This paper focuses on the development of an Industrial Learning Classifier System for Data-Mining in a Steel Hop Strip Mill and the application of Learning Classifiers to the On-Line Reconfiguration of Electric Power Distribution Networks.
Real Options: Managerial Flexibility and Strategy in Resource Allocation
Theory of Self-Reproducing Automata
Principia mathematica, tome I, second édition