scholarly journals The Substrate-Independence Theory: Advancing Constructor Theory to Scaffold Substrate Attributes for the Recursive Interaction between Knowledge and Information

Systems ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
John Turner ◽  
Dave Snowden ◽  
Nigel Thurlow

The substrate-independence theory utilizes sensemaking techniques to provide cognitively based scaffolds that guide and structure learning. Scaffolds are cognitive abstractions of constraints that relate to information within a system. The substrate-independence theory concentrates on the flow of information as the underlying property of the host system. The substrate-independence theory views social systems as complex adaptive systems capable of repurposing their structure to combat external threats by utilizing constructors and substrates. Constructor theory is used to identify potential construction tasks, the legitimate input and output states that are possible, to map the desired change in the substrate’s attributes. Construction tasks can be mapped in advance for ordered and known environments. Construction tasks may also be mapped in either real-time or post hoc for unordered and complex environments using current sensemaking techniques. Mapping of the construction tasks in real-time becomes part of the landscape, and scaffolds are implemented to aid in achieving the desired state or move to a more manageable environment (e.g., from complex to complicated).

2018 ◽  
Vol 11 (1) ◽  
pp. 70-90 ◽  
Author(s):  
Enrique Rubio Royo ◽  
Susan Cranfield McKay ◽  
Jose Carlos Nelson-Santana ◽  
Ramiro N Delgado Rodríguez ◽  
Antonio A. Ocon-Carreras

This article describes a proposal for sustainable way to adapt to current complex process of global transformation, using the ‘Web Knowledge Turbine' (WKT) as a self-organised ecosystem for the co-creation of personal and collective narratives. The authors contemplate all human social systems as Complex Adaptive Systems with the capacity for self-organisation derived from a permanent learning process. Accordingly, a shift in the focus of teaching programmes from mere mechanisms of knowledge transmission, to a process focused on learning and in particular, a process of self-directed, connected, and deep learning which has at its core the profile of the eLearner as the central protagonist. The cornerstone of this process is a Complex Ecosystem of Personal Knowledge (CEPK) which will support teaching at an undergraduate level, progressively and transversely, from its outset. Considering the classroom as a networked community of learners whose objective is not only to gain a command of a particular subject (WHAT content do they need to learn?), but also HOW and WHY they need to learn it.


2019 ◽  
Vol 17 (1) ◽  
pp. 93-109
Author(s):  
Chris Girard

AbstractSpatial boundaries, thermodynamic–economic specialization, and signal processing are at the core of evolution’s major transitions. Centered on these three dimensions, a proposed evolutionary informatics model roots ethnic and racial cleavages in zero-sum contests over rivalrous resources within geophysical sites. As the geophysical boundaries and signal-processing complexity of social systems coevolved, zero-sum contests centered on metropoles extracting resources from hinterlands. In this colonial extraction process, racialization arose from non-market spatial segregation of populations tagged with hinterland lineage. Subsequent post-industrial erosion—and greater permeability—of racial and ethnic boundaries has been enabled by the progressive uncoupling of more highly evolved complex adaptive systems from geophysical location (non-territorial adaptation). Signal and physical topologies are becoming more distinct. This uncoupling from physical location is driven by cybernetic parallelism in complex adaptive systems: diverse and independent agents learning from their mutual exchange of signals. Cybernetic parallelism has generated epistemic and geopolitical challenges to formal apartheid and racializing immigration policies, but not without friction or reversals.


Author(s):  
Kristin Erickson

The chapter considers algorithmic music as the ‘sonification’ of algorithms, a term coined by Carla Scaletti to describe the mapping of numerically represented relations in some domain to relations in an acoustic domain. The chapter looks at the range of ways this concept has been used by the author in composing her works. The chapter identifies isomorphic relationships between algorithms and collaboration, music, and performance, and extends the boundary of the computer to include systems of people and sound. The definition of music and performance is extended to include process, rules, machines, and execution. Examples discussed include performing a bubble sort, pandemic performances (using principles of complex adaptive systems), Mandelbrot music, and M.T.Brain/Telebrain, which send complex algorithmic instructions to multiple performers in real time.


Author(s):  
Roy Williams

Complex Adaptive Systems, for our purposes, are social systems that that evolve and display new, emergent properties, and self-organizing behavior of their components; they are based on a reasonably stable infrastructure, on the satisfaction of the most basic needs, and flexible, frequent, and open communication and interaction. Complex Adaptive Systems may be based on a few, simple rules, but can yield complex and unpredictable outcomes. The ‘Hole in the Wall’ project is an interesting case in point in the design of spaces for complex adaptive systems, or complex adaptive networks. In this project, touch screen computers were literally put in ‘holes in walls’ in places where unschooled children congregated. The children were given no instructions on how to use the computers, or what to do with them, but with startling results: the children soon taught themselves how to use the computers and the Internet, and much more (Mitra, 2003).


Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1330-1354 ◽  
Author(s):  
Maurice Yolles

PurposeComplex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that include Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In Part 1, the purpose of this paper is to identify the conditions for the complementarity of the two classes of theory. In Part 2, the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.Design/methodology/approachA detailed analysis of the literature permits a distinction between hard and softer approaches towards modelling complex social systems. Hard theories are human-incommensurable, while soft ones are human-commensurable, therefore more closely related to the human condition. The characteristics that differentiate between hard and soft approaches are identified.FindingsHard theories are more restrictive than the softer theories. The latter can embrace degrees of “softness” and it is explained how hard and soft approaches can be mixed, sometimes creating Harmony.Originality/valueThere are very few explorations of the relationship between hard and soft approaches to complexity theory, and even fewer that draw in the notion of harmony.


2015 ◽  
Vol 2 (1) ◽  
pp. 65-73 ◽  
Author(s):  
David Large ◽  
Petia Sice ◽  
Robert Geyer ◽  
Geoff O'Brien ◽  
Safwat Mansi

In this paper the authors consider two contrasting viewpoints; Complex responsive processes which deal with interactions in the present, and complex adaptive systems which focus on learning through the production of what are called mental models. The paper shows that rather than being contradictory, these viewpoints are – at least in some respects - complementary. From the resulting perspective we are able to identify qualitative synergies between the two approaches. Complex responsive processes involve reflections on interactions that take place in time. But you cannot stop time so these present reflections always refer back to a present now gone. Complex adaptive systems are analytic tools. They are not explicitly in the present or in time at all, but they shape our thoughts and actions which are in the present. They shape how people behave, respond and think in a context. In this way people can combine, or reorganise, the approach to complex responsive processes and complex adaptive systems to show how humans address the complex notions of our world.


2016 ◽  
Vol 14 (3) ◽  
pp. 177 ◽  
Author(s):  
Lori R. Hodges, MA

This article examines the concept of community fragility in emergency management from a systems perspective. Using literature that addresses fragility in four areas of complex systems, including ecosystems, social systems, sociotechnical systems, and complex adaptive systems, a theoretical framework focused on the emergency management field is created. These findings illustrate how community fragility factors can be used in the emergency management field to not only improve overall outcomes after disaster but also build less fragile systems and communities in preparation for future disasters.


2017 ◽  
Vol 26 (1) ◽  
pp. eR01 ◽  
Author(s):  
Susanna Nocentini ◽  
Gérard Buttoud ◽  
Orazio Ciancio ◽  
Piermaria Corona

Aim of study: The paper is a scientific commented discussion with the aim of defining a framework which allows both a comprehensive vision of forest dynamics, as well as an adaptive management approach and policy procedures more suited to a changing and inherently unpredictable world.Main results: We identify the main challenges facing forestry in relation to recent developments in forestry thinking, i.e. the paradox of aiming at sustainability in a changing environment, a shifting perception of the relationship between ecological and social systems, the recognition of forest ecosystems as complex adaptive systems, the need for integrating the social and ecological dimensions of forestry into a single framework, and the growing awareness of the importance of the ethical approach to the forest. We propose the concept of “systemic forestry” as a paradigm for better understanding forest dynamics and for guiding management and public actions at various levels. We compare the systemic approach with different silvicultural and forest management approaches which have been proposed in the last decades.Research highlights: Our analysis shows that a systemic approach to forestry has five main consequences: 1. forestry is viewed as a part of landscape dynamics through a multi-sectoral coordination, 2. the logic of action changes from norm to process, 3. conservation is a dynamic search for resilience, 4. multi-functionality is achieved through a multi-entries approach integrating ecological, social and economic components of sustainability, 5. forestry institutions are reframed to address the issue of changing interactions among actors, 6. a change in the ethical approach to the forest is needed.


2021 ◽  
pp. 1-18
Author(s):  
Abeba Birhane

Abstract On the one hand, complexity science and enactive and embodied cognitive science approaches emphasize that people, as complex adaptive systems, are ambiguous, indeterminable, and inherently unpredictable. On the other, Machine Learning (ML) systems that claim to predict human behaviour are becoming ubiquitous in all spheres of social life. I contend that ubiquitous Artificial Intelligence (AI) and ML systems are close descendants of the Cartesian and Newtonian worldview in so far as they are tools that fundamentally sort, categorize, and classify the world, and forecast the future. Through the practice of clustering, sorting, and predicting human behaviour and action, these systems impose order, equilibrium, and stability to the active, fluid, messy, and unpredictable nature of human behaviour and the social world at large. Grounded in complexity science and enactive and embodied cognitive science approaches, this article emphasizes why people, embedded in social systems, are indeterminable and unpredictable. When ML systems “pick up” patterns and clusters, this often amounts to identifying historically and socially held norms, conventions, and stereotypes. Machine prediction of social behaviour, I argue, is not only erroneous but also presents real harm to those at the margins of society.


This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book, Adaptation in Natural and Artificial Systems has become a classic text for many disciplines in which adaptation play a central role. The essays brought together here were originally written to honor John Holland, and span most of the different areas touched by his wide-ranging and influential research career. The authors include some of the most prominent scientists in the fields of artificial intelligence evolutionary computation, and complex adaptive systems. Taken together, these essays present a broad modern picture of current research on adaptation as it relates to computers, living systems, society, and their complex interactions.


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