El concepto de poder ha sido uno de los más tradicionales y arraigados de la ciencia política, desde la temprana reflexión de los griegos hasta la actualidad. Es aún hoy un término de extraordinaria vigencia en el lenguaje científico y popular. Sin embargo, cuando indagamos en su real materialidad, advertimos que el mismo es elusivo, confuso y difuso. Desde la emergencia del positivismo, pasando por las revoluciones burguesas, el concepto se mantuvo más o menos inalterado. Con la emergencia del marxismo, (...) de las ideologías modernas y de las escuelas críticas se persiguió su racionalización y redireccionamiento, sin cuestionar la esencia de su significado. Sugerimos que a partir de la Teoría de la Complejidad y de la Teoría de Redes, el concepto podría muy bien dejarse fuera de la ciencia política o quedar limitado sólo a los alcances de la fuerza o coacción. (shrink)

Les études qui portent sur la stigmergie, ou qui l'exploitent pour le développement et la compréhension d'autres objets – comme la cognition sociale, les communs créatifs ou les systèmes adaptatifs complexes par exemple –, connaissent un essor extraordinaire depuis la fin des années 1990 ([11], [12], [22], [38]), essor frappé d'un caractère encore très exploratoire, puisqu'il n'en existe pas à ce jour de théorie unifiée, cohérente et consensuelle. Elle avait pourtant un sens très précis et un...

It is usually assumed in debates about systems thinking, complexity and the philosophy of science that science is primarily about observation. However, the starting point for this paper is intervention, defined as purposeful action by an agent to create change. While some authors suggest that intervention and observation are opposites, it is argued here that observation should be viewed as just one type of intervention. We should therefore welcome scientific techniques of observation into a pluralistic set of intervention methods, alongside (...) methods for exploring values, reflecting on subjective understandings, planning future activities, etc. However, there is a need to explicitly counter a possible pernicious interpretation of this argument: intervention could be viewed as flawlessly pre-planned change based on accurate predictions of the consequences of action. This is the mechanistic world-view that systems thinking and complexity science seek to challenge. Therefore, having redefined scientific observation as intervention, the paper revisits insights from systems thinking and complexity to propose a methodology of systemic intervention. Some brief reflections are then provided on the wider social implications of this methodology. (shrink)

In the article is examined a problem of system and complex approach to management of modern education. The authors emphasize that development of education technology is accompanied by formation of informational, telecommunicational and communicative systems. The development of informationaltechnologies entails the formation of in principle new educational system. This system can ensure millions of people accordance to new educational services. The use of modern computer, telecommunicational and communicative technologies in education intends re-engineering of educational activities, considerablechanges in all its systems. (...) The effectiveness of education is based on the modern technologies. It often depends on quality of use of these technologies for solution of one or another educational task. Innovations in technical system influence the development of educational process. (shrink)

In their recent book, Ladyman and Wiesner (What is a complex system?, Yale University Press, 2020) delineate the bounds of the exciting interdisciplinary field of complexity science. In this work, they provide examples of generally accepted complex systems and common features which these possess to varying degrees. In this paper, I plan to extend their list to include the formal study of natural language, i.e. linguistics. In fact, I will argue that language exhibits many of the hallmarks of a complex (...) system, specifically a complex biological system. Thus, my aim is to advocate contra the the ‘Minimalist Program’ (Chomsky, The minimalist program, MIT Press, Cambridge, 1995), which motivates simple underlying mechanisms (i.e. Merge) in their idealisations, that biolinguistics should embrace a ‘Maximalist Program’ in which multiple subfields contribute component explanations to an emerging whole. (shrink)

Complexity has emerged as the new norm in the 21st century, and IS projects play a significant role in organisations to address various socio-political concerns. The purpose of this paper is to understand what are the relevant constructs for measuring IS project complexity. A model for measuring IS project complexity is developed using PLS-SEM. The model reveals that organisational complexity, technical complexity, and uncertainty underpin IS project complexity. Organisational complexity in terms of project team, stakeholder management, and strategic drive should (...) be managed by the project manager. Technical complexity was established in terms of project goals, requirements management, technology management, and norms and standards. Uncertainty in IS projects exists in terms of skills management, the triple constraint, and activity management. Suggestions were provided to guide IS project managers on how to manage each construct and alleviate the level of project complexity. This paper presents an updated and different perspective on measuring and managing IS project complexity. The findings would serve as additional building blocks to further elucidate IS project complexity understanding and assist with improving the value of these projects. Furthermore, the suggestions for IS project managers can lead discussions around how IS projects should be managed to ensure complexity is under control. (shrink)

Here, for the first time, development studies encounters the set of ideas popularly known as 'Chaos Theory'. Samir Rihani applies to the processes of economic development, ideas from complex adaptive systems like uncertainty, complexity, and unpredictability. Rihani examines various aspects of the development process - including the World Bank, debt, and the struggle against poverty - and demonstrates the limitations of fundamentally linear thinking in an essentially non-linear world.

In [5] we study Nonassociative Lambek Calculus augmented with De Morgan negation, satisfying the double negation and contraposition laws. This logic, introduced by de Grooté and Lamarche [10], is called Classical Non-Associative Lambek Calculus. Here we study a weaker logic InNL, i.e. NL with two involutive negations. We present a one-sided sequent system for InNL, admitting cut elimination. We also prove that InNL is PTIME.

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second line of research used more simple, (...) knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

In _Complexity and Postmodernism_, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory into his discussion. _Complexity and Postmodernism_ is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, (...) cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales. (shrink)

When we deal with complex things, like human subjects or organizations, we deal with identity – that which makes a person or an organization what it is and distinguishes him/her/it from other persons or organizations, a kind of “self”. Our identity determines how we think about and interact with others. It will be argued in this chapter that the self is constituted relationally. Moreover, when we are in the realm of the self, we are always already in the realm of (...) engaging with and mediating differences – the realm of ethics. The position which will be developed argues that approaching identity as a complex system allows us to resist thinking of identity as an easily identifiable and static entity. Identity is always being constituted within a complex and contingent world, where we have to make choices based on contingent values rather than on universal knowledge or the outcome of rational calculations. As a result, we have to keep in mind that our daily practices always already have an ethical component, and our decisions need to be continually evaluated and re-evaluated in the light of our (and others’) varying identities. (shrink)

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...) Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

This paper discusses the epistemic status of biology from the standpoint of the systemic approach to living systems based on the notion of biological autonomy. This approach aims to provide an understanding of the distinctive character of biological systems and this paper analyses its theoretical and epistemological dimensions. The paper argues that, considered from this perspective, biological systems are examples of emergent phenomena, that the biological domain exhibits special features with respect to other domains, and that biology as a discipline (...) employs some core concepts, such as teleology, function, regulation among others, that are irreducible to those employed in physics and chemistry. It addresses the claim made by Jacques Monod that biology as a science is marginal. It argues that biology is general insofar as it constitutes a paradigmatic example of complexity science, both in terms of how it defines the theoretical object of study and of the epistemology and heuristics employed. As such, biology may provide lessons that can be applied more widely to develop an epistemology of complex systems. (shrink)

In this paper the central ideas and history of the theory of complex systems are described. It is shown how this theory lends itself to different interpretations and, correspondingly, to different political conclusions.

Ecologist Richard Levins argues population biologists must trade-off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...) Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

Consciousness has been the bone of contention for philosophers throughout centuries. Indian philosophy largely adopted lived experience as the starting point for its explorations of consciousness. For this reason, from the very beginning, experience was an integral way of grasping consciousness, whose validity as a tool was considered self-evident. Thus, in Indian philosophy, the question was not to move from the brain to mind but to understand experience of an individual and how such an experience is determined through mental structures (...) (and secondarily, the preoccupation with the brain and its relation to the mind). In contrast, cognitive science (the study of mind and cognition through 1 interdisciplinary methods, with emphasis on computational methods) found its debates soaked in discussion which primarily involved the brain and mind. Experience was not considered a primary source of information and its validity had to be established to consider it a source of information of mind. With the rise of physicalism and realization that mental states are correlative to brain states, the body was virtually neglected from involvement in understanding the mind and the attempts to reduce mind to the brain were rampant. The inability to explain subjective experience of an individual through neuroscientific findings alone has urged philosophers to explore other ways of understanding the ontology of mind. Over the last few years, embodied cognition and enactive approach have brought back the body as a central participant in this debate, providing fertile grounds to explain the relation of brain, body and mind. This paper proposes that we understand the brain as a complex system from which the mind emerges. This emergence is marked by the development of novel property of self-consciousness in human beings. The mind is a process which is embedded throughout the body and thus, the body acts as an actualizing medium for the individual. Thus, the brain is a necessary condition for the mind to be while the mind is embedded throughout the body. The brain and mind are in reciprocal causal relationship with one another, as is the body and environment with one another. In this paper, embodied cognition is understood through principles of Merleau Ponty's idea of embodiment, than through Andy Clark and Francis Varela's alone. (shrink)

Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...

The complex systems approach (CSA) to characterizing cognitive function is purported to underlie a conceptual and methodological revolution by its proponents. I examine one central claim from each of the contributed papers and argue that the provided examples do not justify calls for radical change in how we do cognitive science. Instead, I note how currently available approaches in ‘‘standard’’ cognitive science are adequate (or even more appropriate) for understanding the CSA provided examples.

Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues (...) that intentional control needs to be seen as a particular type of relationship between the system and its environment. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...) handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

In this paper we propose the multiple complex systems approach for assessing domain-general complex problem-solving skills and its processes knowledge acquisition and knowledge application. After defining the construct and the formal frameworks for describing complex problems, we emphasise some of the measurement issues inherent in assessing CPS skills with single tasks. With examples of the MicroDYN test and the MicroFIN test, we show how to adequately score problem-solving skills by using multiple tasks. We discuss implications for problem-solving research and the (...) assessment of CPS skills in general. (shrink)

Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with complex systems in (...) the literature and by those in the field. We argue that some of these features are neither necessary nor sufficient for complexity, and that some of them are too vague or confused to be of any analytical use. In order to bring mathematical rigour to the issue we then review some standard measures of complexity from the scientific literature, and offer a taxonomy for them, before arguing that the one that best captures the qualitative notion of the order produced by complex systems is that of the Statistical Complexity. Finally, we offer our own list of necessary conditions as a characterization of complexity. These conditions are qualitative and may not be jointly sufficient for complexity. We close with some suggestions for future work. (shrink)

In this paper, we focus attention on the role of computer system complexity in ascribing responsibility. We begin by introducing the notion of technological moral action (TMA). TMA is carried out by the combination of a computer system user, a system designer (developers, programmers, and testers), and a computer system (hardware and software). We discuss three sometimes overlapping types of responsibility: causal responsibility, moral responsibility, and role responsibility. Our analysis is informed by the well-known accounts provided by Hart and Hart (...) and Honoré. While these accounts are helpful, they have misled philosophers and others by presupposing that responsibility can be ascribed in all cases of action simply by paying attention to the free and intended actions of human beings. Such accounts neglect the part played by technology in ascriptions of responsibility in cases of moral action with technology. For both moral and role responsibility, we argue that ascriptions of both causal and role responsibility depend on seeing action as complex in the sense described by TMA. We conclude by showing how our analysis enriches moral discourse about responsibility for TMA. (shrink)

This is a review article of Paul Cillier's 1999 book _Complexity and Postmodernism_. The review article is generally encouraging and constructive, although isolates a number of areas in need of clarification or development in Cillier's work. The volume of the _South African Journal of Philosophy_ in which the review article appeared also printed a response by Cilliers.

Despite the close connection between the central limit theorem and renormalization group (RG) methods, the latter should be considered fundamentally distinct from the kind of probabilistic framework associated with statistical mechanics, especially the notion of averaging. The mathematics of RG is grounded in dynamical systems theory rather than probability, which raises important issues with respect to the way RG generates explanations of physical phenomena. I explore these differences and show why RG methods should be considered not just calculational tools but (...) the basis for a physical understanding of complex systems in terms of structural properties and relations. (shrink)

This article contributes to the revision of the concept of system in social theory using complexity theory. The old concept of social system is widely discredited; a new concept of social system can more adequately constitute an explanatory framework. Complexity theory offers the toolkit needed for this paradigm shift in social theory. The route taken is not via Luhmann, but rather the insights of complexity theorists in the sciences are applied to the tradition of social theory inspired by Marx, Weber, (...) and Simmel. The article contributes to the theorization of intersectionality in social theory as well as to the philosophy of social science. It addresses the challenge of theorizing the intersection of multiple complex social inequalities, exploring the various alternative approaches, before rethinking the concept of social system. It investigates and applies, for the first time, the implications of complexity theory for the analysis of multiple intersecting social inequalities. Key Words: complexity theory • inequality • intersectionality • social theory. (shrink)

This article aims to study the intersection between critical realism and complexity theories through the existing literature on complex systems via an engagement with Luhmann’s autopoiesis. With reference to the philosophies of substance and persistence, I build on previous critical realist scholarship and provide an explanation for what the literature has only noted as the limitations and potentials of autopoiesis for complex systems thinking and its compatibility with Critical Realism. By highlighting how Luhmann’s autopoiesis is not a trans-immanent/ perdurantist-exdurantist system, (...) I show first how a trans immanent system through the method of calibration entails a complex causation involving objects in the environment of systems and not just within their boundaries. Second, I explain how a trans-immanent system fits with CR via the Morphogenetic Régulation framework by exploring the theme of crisis in terms of the movement from inadequate to adequate understanding of objects. (shrink)

Complexity science has witnessed a number of advances since the publication of Jervis's System Effects. These advances better allow us to untangle the messy elements in a system and predict sets of likely outcomes. However, just because a system is complex doesn't mean that all the ideas relating to complexity—such as agent-based modeling, path dependency, tipping points, between-class versus within-class effects, and networks—are necessarily relevant. One of our tasks is to determine whether they are—and, if so, their implications. As examples, (...) we use China's role in the formation of the United States housing bubble; the federal government's bailout of AIG and Bear Stearns but not Lehman Brothers; and China's failure to experience a regime change such as the Middle East's Arab Spring. (shrink)

The arts are one of the most complex of human endeavours, and so it is fitting that a special issue on Complex Systems in Aesthetics and Arts is being published. As the editors of this special issue, we would like to thank the reviewers of the submitted papers for their hard work in making this issue possible, as well as the authors who submitted their work and were very responsive to the comments of the reviewers and editors.

Regularities in natural language systems, despite their cognitive advantages in terms of storage and learnability, often coexist with exceptions, raising the question of whether and why irregularities survive. We offer a complex system perspective on this issue, focusing on the irregular past tense forms in English. Two separate processes affect the overall regularity: new verbs constantly entering the vocabulary in the regular form at low frequency, and transitions in both directions occurring in a narrow frequency range. The introduction of new (...) verbs leads to an increase in regular types, that, entering at low frequencies, have a small impact on the perceived irregularity in terms of tokens. The frequency of usage acts as a control parameter, the majority of verbs types being fully-regular at low frequencies, with no evidence of irregularity facing extinction. Very few verbs types in an intermediate frequency region exhibit both regular and irregular forms at the same time, suggesting that the coexistence is unstable. The observed pattern of usage showing an abrupt change in response to small variations of the control parameter only appears in agent-based models provided that the word state is non-binary. By introducing this key ingredient, high-frequency irregular past-tense can survive the tendency to regularize over time, as observed in natural languages. (shrink)

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in a variety (...) of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. (shrink)

A multitude of global challenges that society grapples with, including climate change, social injustices, and economic disparities, persist largely due to the shortcomings of effectively responding to complex systems. In this article, we consider adopting systems literacy as a comprehensive educational approach to navigate in complex systems. We advocate for a systems literacy pedagogy that employs an affective-relational-cognitive (ARC) framework for learning, emphasizing active engagement and intervention in the world. The concept of systems beings is rooted in both ontological education (...) and systems literacy, and we propose the ARC framework as both a pedagogical theory and practice to further understand and engage with it. This is further explored through an educational example of a transdisciplinary doctoral pilot project focused on the climate emergency. (shrink)