We introduce a spatial model of concentration dynamics that supports the emergence of spatiotemporal inhomogeneities that engage in metabolism–boundary co-construction. These configurations exhibit disintegration following some perturbations, and self-repair in response to others. We define robustness as a viable configuration’s tendency to return to its prior configuration in response to perturbations, and plasticity as a viable configuration’s tendency to change to other viable configurations. These properties are demonstrated and quantified in the model, allowing us to map a space of viable configurations and their possible transitions. Combining robustness and plasticity provides a measure of viability as the average expected survival time under ongoing perturbation, and allows us to measure how viability is affected as the configuration undergoes transitions. The framework introduced here is independent of the specific model we used, and is applicable for quantifying robustness, plasticity, and viability in any computational model of artificial life that demonstrates the conditions for viability that we promote.

Key words: autopoiesis, viability, robustness, plasticity, spatial dynamical system, metabolism

Purpose: Complexity is the real beast that baffles everybody. Though there are increasing inter-disciplinary discussions on it, yet it is scantly explored. The purpose of this paper is to bring a new and unique dimension to the discourse assimilating the important ideas of two towering scientists of their time, Newton and Heinz von Foerster. In the tradition of Foersterian second-order cybernetics the paper attempts to build a bridge from a cause-effect thinking to a thinking oriented towards “understanding understanding” and in the process presents a model of “Cybernetics of Simplification” indicating a path to simplicity from complexity. Design/methodology/approach – The design of research in the paper is exploratory and the paper takes a multidisciplinary approach. The model presented in the paper builds on analytics and systemics at the same time. Findings: Simplicity can be seen in complex systems or situations if one can construct the reality (be that the current one that is being experienced or perceived or the future one that is being desired or envisaged) through the Cybernetics of Simplification model, establishing the effect-cause-and-effect and simultaneously following the frame of iterate and infer as a circular feedback loop; in the tradition of cybernetics of cybernetics. Research limitations/implications – It is yet to be applied. Practical implications: The model in the paper seems to have far reaching implications for complex problem solving and enhancing understanding of complex situations and systems. Social implications – The paper has potential to provoke new ideas and new thinking among scholars of complexity. Originality/value – The paper presents an original idea in terms of Cybernetics of Simplification building on the cybernetics of the self-observing system. The value lies in the unique perspective that it brings to the cybernetics discussions on complexity and simplification.

Key words: causality, complexity, second-order cybernetics, cybernetics of simplification, self-observing system, simplification

The concept of autonomy is of crucial importance for understanding life and cognition. Whereas cellular and organismic autonomy is based in the self-production of the material infrastructure sustaining the existence of living beings as such, we are interested in how biological autonomy can be expanded into forms of autonomous agency, where autonomy as a form of organization is extended into the behaviour of an agent in interaction with its environment (and not its material self-production) In this thesis, we focus on the development of operational models of sensorimotor agency, exploring the construction of a domain of interactions creating a dynamical interface between agent and environment. We present two main contributions to the study of autonomous agency: First, we contribute to the development of a modelling route for testing, comparing and validating hypotheses about neurocognitive autonomy. Through the design and analysis of specific neurodynamical models embedded in robotic agents, we explore how an agent is constituted in a sensorimotor space as an autonomous entity able to adaptively sustain its own organization. Using two simulation models and different dynamical analysis and measurement of complex patterns in their behaviour, we are able to tackle some theoretical obstacles preventing the understanding of sensorimotor autonomy, and to generate new predictions about the nature of autonomous agency in the neurocognitive domain. Second, we explore the extension of sensorimotor forms of autonomy into the social realm. We analyse two cases from an experimental perspective: the constitution of a collective subject in a sensorimotor social interactive task, and the emergence of an autonomous social identity in a large-scale technologically-mediated social system. Through the analysis of coordination mechanisms and emergent complex patterns, we are able to gather experimental evidence indicating that in some cases social autonomy might emerge based on mechanisms of coordinated sensorimotor activity and interaction, constituting forms of collective autonomous agency.

Over the past decades many teaching strategies have been proposed by various educators to improve education of all students including students with special needs. No single one of these proposed teaching strategies meets the needs of all students. The new Every Student Succeeds Act, successor to No Child Left behind Law, which transfers oversight from federal level back to states, could be a benefactor for constructivism and special education. Educators are also optimistic that the new Every Student Succeeds Act will be better for vulnerable students in special education because it will introduce more flexibility in how individual states carry out evaluation of students and teachers. In addition, it will provide more flexibility on testing and adapt the curriculum to student’s needs. It would further reduce time and energy for students preparing for standardized tests or statewide exams. It will also end “Adequate Yearly Progress” – a measure that required schools to show test score gains. Constructivist teaching philosophy is all about accepting student autonomy where student thinking drives the lessons, where dialogue, inquiry, and puzzlement are valued and assessing student learning is in the context of teaching. It helps teachers to draw on new ideas as they make decisions about which teaching techniques are most appropriate for all students to learn. Now is the time to revisit the great debate of constructivism versus teacher-centered instruction and special education. Time has come to effectively explore our educational system and examine the core unit of the whole enterprise, the textbook, the classroom, a setting that is often dominated by teacher talk and students listen.

Key words: constructivist teaching strategies, student with special needs, academic outcomes, students with learning disabilities, positive learning, policy makers, indirect instruction, every student succeeds act.

Personal construct and family systems theories can profit from an exchange of ideas concerning the relationship between their personal and interpersonal aspects of construction. This article examines three possible points of contact between the two orientations. First, we suggest that personal construct psychology could profit from addressing the important contributions of the family context to the development of each individual’s system. Second, we address the impact of the person’s constructions on the larger family system. Third, we suggest that the family system itself develops a system of shared constructions that define and bind its identity and interactions. Each of these areas of interface carries implications for therapy, and specific intervention techniques corresponding to each of these are discussed.

This paper defines a theoretical framework aiming to support the actions and reflections of researchers looking for a “method” in order to critically conceive the complexity of a scientific process of research. First, it starts with a brief overview of the core assumptions framing Morin’s “paradigm of complexity” and Le Moigne’s “general system theory.” Distinguishing “methodology” and “method,” the framework is conceived based on three moments, which represent recurring stages of the spiraling development of research. The first moment focuses on the definition of the research process and its sub-systems (author, system of ideas, object of study and method) understood as a complex form of organization finalized in a specific environment. The second moment introduces a matrix aiming to model the research process and nine core methodological issues, according to a programmatic and critical approach. Using the matrix previously modeled, the third moment suggests conceiving of the research process following a strategic mindset that focuses on contingencies, in order to locate, share and communicate the path followed throughout the inquiry. Relevance: This paper provides the readers with a constructivist methodology of research inspired by Morin’s paradigm of complexity and Le Moigne’s general system theory.

Excerpt: In Radicalizing Enactivism (RE), Hutto and Myin present compelling arguments for why basic minds do not have content. In particular, they introduce the Hard Problem of Content (HPC), which states that ‘informational content is incompatible with explanatory naturalism’ (xv). By reviewing a range of theories, the pair demonstrate the futility of attempts to distinguish content from covariance (content is information within a system, whereas a covariant system can be explained purely by way of causal interactions).

This paper undertakes a theoretical investigation of the “learning” aspect of science as opposed to the “knowledge” aspect. The practical background of the paper is in agricultural systems research – an area of science that can be characterised as “systemic” because it is involved in the development of its own subject area, agriculture. And the practical purpose of the theoretical investigation is to contribute to a more adequate understanding of science in such areas, which can form a basis for developing and evaluating systemic research methods, and for determining appropriate criteria of scientific quality. Two main perspectives on science as a learning process are explored: research as the learning process of a cognitive system, and science as a social, communicational system. A simple model of a cognitive system is suggested, which integrates both semiotic and cybernetic aspects, as well as a model of self-reflective learning in research, which entails moving from an inside “actor” stance to an outside “observer” stance, and back. This leads to a view of scientific knowledge as inherently contextual and to the suggestion of reflexive objectivity and relevance as two related key criteria of good science.

Key words: Agriculture, cognition, communication, experiential, learning, research, science, self-reflective, systemic

Upshot: In our response we focus on five questions that point to important common themes in the commentaries: why start in wicked problems, what kind of system is a scientific perspective, what is the nature of second-order research processes, what does this mean for understanding interdisciplinary work, and how may polyocular research help make real-world decisions.

Natural systems cannot be closed to the environment. At the same time there is a necessity for closure in order to build the system. It is this quintessential tension between openness and closure that drives systems to unfold into further stages or levels of growth and development. In other words, the emergence of organization in natural systems is a result of cycles of openness and closure. There are two distinct and complementary ways by which a system will carry over closure while involved in a process of expansion across the environment. These two ways need to be expressed in any formal representation: (1) within a level this will be by means of transitive closure, which is additive; and (2) between levels (i.e., from one level to the next higher level) this requires algebraic closure, which is multiplicative. The former expresses space closure, whereas the latter expresses topological or time closure. The conjunction of these two closures generates a hierarchy of levels. Prior to, and outside of, the system lies semantic closure.