John H. Holland: Signals and boundaries: building blocks for complex adaptive systems

2013 ◽  
Vol 14 (2) ◽  
pp. 279-280
Author(s):  
Denis Robilliard
Author(s):  
John H. Holland

What is a niche? ‘Co-evolution and the formation of niches’ explains that the term ‘niche’ is widely used to describe an important part of the hierarchical organization of complex adaptive systems: local use of signals and resources. Using Markov processes, a mathematical theory of niches can be formed that allows for multiple species with interaction networks that involve loops and recirculation. When realistic niches are considered, the diversity of the niche dwellers stands out. We see a complicated recirculation of resources and signals. How did this complex network of interactions evolve? The short answer is co-evolution through recombination of building blocks, often accompanied by an exaggeration of some of the resulting characteristics.


2020 ◽  
Vol 16 (35) ◽  
Author(s):  
Andrei-Razvan Coltea

Complexity is a paradigm whose relevance is currently expanding beyond the domain of ‘hard’ sciences. Humanities and social sciences could greatly benefit from using it as an antidote to reductionism, and religious studies in particular is a field in great need of defragmentation and a broader theoretical perspective. This paper’s ambitious aim is to propose such a perspective while frequently crossing interdisciplinary borders and, by drawing inspiration from and criticizing the work of evolutionary anthropologist Richard Sosis, to offer an integrative analytical framework for the study of religions as allopoietic complex adaptive systems. Firstly, this paper describes the core features of complex systems (non-linear, autopoietic/allopoietic, entropy reducing, open, adaptive, emergent). Secondly, it identifies religions as abstract complex systems and their basic components as signal/noise distinctions of informational inputs from the environment. More importantly, it posits that they fulfill an entropy reducing function in psychic systems by the emergence of meaning. Lastly, it builds a model of religious systems and identifies six building blocks: rituals, myths, taboos, supernatural agents, authority and afterlife beliefs, following Luhmann in claiming that individuals are not part of the system, but of the environment. Consequently, the cooperative behavior of individuals to form social structures cannot constitute the ultimate output of the system, but only a behavioral effect of the actual one, meaning.


2011 ◽  
Vol 328-330 ◽  
pp. 970-973
Author(s):  
Yong Gui Shi ◽  
Jian Fen Yan

Based on the analysis of complex adaptive systems theory and classification of enterprise network, the article proposes that the enterprise network is a kind of CAS. Although the enterprise network has a variety of forms, they all have the basic characteristics of CAS: Aggregation, Identification, Nonlinear, Stream, Diversity, Internal model and Building blocks. The article discusses the complex adaptive features of the enterprise network which includes has active adaptive, multi-hierarchy nature, open, non-linear (butterfly effect), synergy and learning together and other characteristics, the enterprise network is made of a number of agents who are relatively autonomous and intelligent, each node enterprise in the enterprise network can be regarded as independent intelligent agents, in general the agents operate independently or semi-autonomous based on their own goal and ability of decision-making, as part of the system, these agents and their behavior have a high degree of coupling or dependency, the integrated level of system will depend on the coordination of the dependence. So the article gives the behavior model of enterprise network agents.


Author(s):  
Rick L. Riolo ◽  
Michael D. Cohen

There are several key ideas that appear in almost all of John Holland's writings on artificial and natural complex adaptive systems: internal models, default hierarchies, genetic (evolutionary) algorithms, and recombination of building blocks. One other mechanism, which is linked to all of those, is tag-based interaction. Perhaps the first use of tag-based interaction (though it was not so named) can be found in Holland's "broadcast system," [26] a formal specification of an architecture suitable for modeling adaptation of open-ended, parallel processes. Tag-based interaction mechanisms next played a key role in classifier systems [30, 32]. In classifier systems, a tag acts as a kind of "address" of one or more classifier rules (productions), enabling rules to send messages to selected sets of rules, and allowing rules to select which messages they will respond to. Thus, tags provide a way to structure computations, making it possible to prove that classifier systems are computationally complete [18], to various neural network architectures [8, 55] and even to abstract models of immune systems [17]. Tags also are used to form coupled chains of classifiers, to construct subroutinelike structures, and to allow Holland's Bucket Brigade algorithm to efficiently allocate credit to "stage setting" rules [9, 30, 50]. Holland has also described how tagged classifiers might be used to form default hierarchies and other more complex internal models [28, 30, 33, 46]. More generally, Holland has emphasized the key role that tag-based interaction mechanisms have in almost all complex adaptive systems (CAS), i.e., systems composed of limited capability agents who interact to generate systemlevel behavior [31]. In the context of CAS, tags are arbitrary properties or traits of agents which are visible to other agents, and which agents can detect and use to condition reactions to other tag-carrying agents. Tags can be agent features, such as surface markings, or they can be agent behaviors, from behavioral routines in animals to more complex behaviors of humans, e.g., wearing particular clothes, carrying flags, or following religious customs [3, 31, 53]. Since agents can have different tags, and since arbitrary tags can come to be associated with particular types of agents (with their own interaction and behavioral patterns), tags can take on "meanings" by virtue of the types of agents who display each particular tag, i.e., as a result of the other behavioral traits those agents tend to have.


Author(s):  
Charles Nelson

Using John Holland’s model of complex adaptive systems, this paper explores how nonnative speakers of English learned to participate and to write in a first-year university rhetoric and composition course. Of particular interest is the emergence of students’ internal models for writing and other class tasks through the reproduction and cross-over of conceptual building blocks, showing that much of learning and creativity is due to recombining what is known rather than invention de novo. The findings in this paper suggest that educators should design curricula around core conceptual building blocks that can be combined in various ways across novel situations and that can lead to an ongoing emergence of new building blocks.


2018 ◽  
Vol 373 (1744) ◽  
pp. 20170163 ◽  
Author(s):  
C. Robert Cloninger ◽  
Igor Zwir

There is fundamental doubt about whether the natural unit of measurement for temperament and personality corresponds to single traits or to multi-trait profiles that describe the functioning of a whole person. Biogenetic researchers of temperament usually assume they need to focus on individual traits that differ between individuals. Recent research indicates that a shift of emphasis to understand processes within the individual is crucial for identifying the natural building blocks of temperament. Evolution and development operate on adaptation of whole organisms or persons, not on individual traits or categories. Adaptive functioning generally depends on feedback among many variable processes in ways that are characteristic of complex adaptive systems, not machines with separate parts. Advanced methods of unsupervised machine learning can now be applied to genome-wide association studies and brain imaging in order to uncover the genotypic–phenotypic architecture of traits like temperament, which are strongly influenced by complex interactions, such as genetic epistasis, pleiotropy and gene–environment interactions. We have found that the heritability of temperament can be nearly fully explained by a large number of genetic variants that are unique for multi-trait profiles, not single traits. The implications of this finding for research design and precision medicine are discussed. This article is part of the theme issue ‘Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.


2017 ◽  
Vol 14 (6) ◽  
pp. 1071-1096 ◽  
Author(s):  
DAVID A. HARPER ◽  
ANTHONY M. ENDRES

AbstractWe examine brand building from the perspective of complex adaptive systems. Brand building is a neglected engine of capital formation, innovation and institutional change in market economies. The nature of brands and the service streams they generate have been construed too narrowly. Brands are capital: entrepreneurs use brands as market-making devices that create value and capture profit, while consumers use brands to derive psychic income and lifestyle benefits. Brands are building blocks that can be combined in production to fill perceived gaps in brand architectures and capital structures. These structures are themselves complex adaptive systems. In an era of digital technological platforms, complex generative networks are the institutional locus of brand creation and brand extensions. Innovation in brand building is a socially distributed, service-intensive and interpretive process; it entails combinatorial experiments in resource integration by heterogeneous and socially connected actors, such as entrepreneur-producers, end-users and distributors. Legal brand owners never have total control over their brands – customer networks often exercise substantial de facto control rights (economic property rights) over the use and transformation of brands. Both the entire branding system (as a form of organization) and individual iconic brands can crystallize into relatively stable institutions that orient and coordinate market behaviour.


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