Search Results (59)

A special class of complex adaptive systems—biological and social—thrive not by passively accumulating patterns, but by engineering coherence, i.e., the deliberate alignment of prior knowledge, real-time updates, and teleonomic purposes. By contrast, today’s AI stacks—Large Language Models (LLMs) wrapped in agentic toolchains—remain rooted in a Turing-paradigm architecture: statistical world models (opaque weights) bolted onto brittle, imperative workflows. They excel at pattern completion, but they externalize governance, memory, and purpose, thereby accumulating coherence debt—a structural fragility manifested as hallucinations, shallow and siloed memory, ad hoc guardrails, and costly human oversight. The shortcoming of current AI relative to human-like intelligence is therefore less about raw performance or scaling, and more about an architectural limitation: knowledge is treated as an after-the-fact annotation on computation, rather than as an organizing substrate that shapes computation. This paper introduces Mindful Machines, a computational paradigm that operationalizes coherence as an architectural property rather than an emergent afterthought. A Mindful Machine is specified by a Digital Genome (encoding purposes, constraints, and knowledge structures) and orchestrated by an Autopoietic and Meta-Cognitive Operating System (AMOS) that runs a continuous Discover–Reflect–Apply–Share (D-R-A-S) loop. Instead of a static model embedded in a one-shot ML pipeline or deep learning neural network, the architecture separates (1) a structural knowledge layer (Digital Genome and knowledge graphs), (2) an autopoietic control plane (health checks, rollback, and self-repair), and (3) meta-cognitive governance (critique-then-commit gates, audit trails, and policy enforcement). We validate this approach on the classic Credit Default Prediction problem by comparing a traditional, static Logistic Regression pipeline (monolithic training, fixed features, external scripting for deployment) with a distributed Mindful Machine implementation whose components can reconfigure logic, update rules, and migrate workloads at runtime. The Mindful Machine not only matches the predictive task, but also achieves autopoiesis (self-healing services and live schema evolution), explainability (causal, event-driven audit trails), and dynamic adaptation (real-time logic and threshold switching driven by knowledge constraints), thereby reducing the coherence debt that characterizes contemporary ML- and LLM-centric AI architectures. The case study demonstrates “a hybrid, runtime-switchable combination of machine learning and rule-based simulation, orchestrated by AMOS under knowledge and policy constraints”. Full article

Thermodynamic laws and principles overarch all domains of physics, chemistry and biology. In this broad perspective, further generalizations with respect to the “state-of-the-art” of current theories are still viable considering all aspects of systems’ states and phenomena. This research aims to discuss the physical and informational implications of Carnot and Joule cycles and the properties inferred from their definitions, as well as the extrema principles governing non-equilibrium phenomena in complex systems. The approach adopted can be viewed as an analytical variational method focusing cycles’ performances and maxima of properties and parameters along cyclic processes. The dualisms and symmetries characterizing Carnot and Joule cycles imply the inference of the necessity and sufficiency of the stable equilibrium for equality of thermodynamic potentials of any system in any state. The conclusions provide a perspective on complex systems and non-equilibrium processes governed by the extrema principles and the physical and informational properties relating to complexity and self-organization. This treatise also represents a basis and a proposal for further developments looking forward to unifying thermodynamic and informational aspects of extrema principles in the direction of complexity, self-organization, constructal emergence and autopoiesis of non-living and living systems in the frame of a general unifying paradigm. Implications and applications are envisaged in an extended perspective accounting for sustainability, circularity and biotechnologies representing future scenarios of industry and environmental protection. Full article

The increasing intersection of psychotherapy, cognitive science, neuroscience, and systems engineering beckons us to rethink what it means to talk the language of the human mind in the clinical setting. This position paper proposes the idea of entangled autopoiesis, a metatheoretical paradigm that addresses the mind and therapy not as linear processes but as self-organizing, adaptive processes enfolded across neural, cognitive, relational, and cultural domains. Psychotherapy, from this viewpoint, is less a corrective technique and more a zone of systemic integration, wherein resilience and meaning are co-created in the interaction of embodied brains, lived stories, and relational fields. Neuroscience informs us about plasticity and regulation; cognitive science emphasizes the embodied and extended nature of cognition; and systems engineering sheds light on feedback, emergence, and adaptive dynamics. Artificial intelligence appears as a double presence: as a metaphor for complexity and as a practical tool able to chart patterns below human sensibility. By adopting a complexity-aware epistemology, we advocate a relocation in clinical thinking—one recognizing the psyche as an autopoietic network, entangled with culture and technology and able to renew itself in therapeutic encounters. The implications for clinical methodology, therapist training, and future interdisciplinary research are discussed. Full article

As artificial intelligence advances toward unprecedented capabilities, society faces a choice between two trajectories. One continues scaling transformer-based architectures, such as state-of-the-art large language models (LLMs) like GPT-4, Claude, and Gemini, aiming for broad generalization and emergent capabilities. This approach has produced powerful tools but remains largely statistical, with unclear potential to achieve hypothetical “superintelligence”—a term used here as a conceptual reference to systems that might outperform humans across most cognitive domains, though no consensus on its definition or framework currently exists. The alternative explored here is the Mindful Machines paradigm—AI systems that could, in future, integrate intelligence with semantic grounding, embedded ethical constraints, and goal-directed self-regulation. This paper outlines the Mindful Machine architecture, grounded in Mark Burgin’s General Theory of Information (GTI), and proposes a post-Turing model of cognition that directly encodes memory, meaning, and teleological goals into the computational substrate. Two implementations are cited as proofs of concept. Full article

Intelligence is a central topic in computing and philosophy, yet its origins and biological roots remain poorly understood. The framework proposed in this paper approaches intelligence as the complexification of agency across multiple levels of organization—from active matter to symbolic and social systems. Agents gradually acquire the capacity to detect differences, regulate themselves, and sustain identity within dynamic environments. Grounded in autopoiesis, cognition is reframed as a recursive, embodied process sustaining life through self-construction. Intelligence evolves as a problem-solving capacity of increasing organizational complexity: from physical self-organization to collective and reflexive capabilities. The model integrates systems theory, cybernetics, enactivism, and computational approaches into a unified info-computational perspective. Full article

Systems-of-systems are often characterized as systems where the constituent parts have some independence from the whole. Recent research has aimed at clarifying in more detail what this independence means. It has shown that independence requires the constituent systems to be agents that observe the system-of-systems from within and construct internal models of it as a basis for decisions. This view on observers as parts of the system-of-systems parallels development in the field of second-order cybernetics several decades ago, yet the connection between that field and systems-of-systems has not been explored previously. This paper, therefore, summarizes key concepts from second-order cybernetics, including the subtopic autopoiesis. It then discusses what the implications are on systems-of-systems engineering through the identification of 17 concerns. These concerns relate to the physical topology, behavior, and control of the system-of-systems. This paper shows how these concerns directly relate to the theoretical concepts of second-order cybernetics and autopoiesis, and thereby, opens the door to further exploitation of this theoretical foundation. Full article

For over a century, the somatic gene mutation theory of cancer has been a scientific orthodoxy. The recent failures of causal explanations using this theory and the lack of significant progress in addressing the cancer problem medically have led to a new competition of ideas about just what cancer is. This essay presents an alternative view of cancer as a developmental process gone wrong. More specifically, cancer is a breakdown in the autopoietic process of organ maintenance and the multicellular coordination of tissues. Breast cancer is viewed through a systems science perspective as an example of the importance of framing one’s theoretical assumptions before making empirical judgments. Finally, a new understanding of the histoarchitecture of the interstitium is presented as a first principle of cancer: a process of cells coming from cells, invading the space between cells. Full article

School is often said to be a representation of society because its primary aim is to promote integration into society. This study of the landscape elements of minority language schools suggests that this type of linguistic landscape may not only reflect a change in linguistic dominance but can also play a complementary role compared to the external, out-of-school world. In this paper, the authors attempt to explore a new way of interpreting the notion of the linguistic landscape of schools. The novelty of this approach lies in the application of a spatial theoretical concept, where the schoolscape is defined as an element of autopoietic space—a self-constituting spatial element. Within this autopoietic framework, markers of ethnolinguistic vitality in the linguistic landscape of minority language schools are identified, and a set of criteria is established that can be applied to other communities. The conclusions are drawn from a comparative analysis of the linguistic landscapes of Hungarian-medium schools in Romania, Slovakia, and Slovenia. Full article

Biological systems have a unique ability inherited through their genome. It allows them to build, operate, and manage a society of cells with complex organizational structures, where autonomous components execute specific tasks and collaborate in groups to fulfill systemic goals with shared knowledge. The system receives information from various senses, makes sense of what is being observed, and acts using its experience while the observations are still in progress. We use the General Theory of Information (GTI) to implement a digital genome, specifying the operational processes that design, deploy, operate, and manage a cloud-agnostic distributed application that is independent of IaaS and PaaS infrastructure, which provides the resources required to execute the software components. The digital genome specifies the functional and non-functional requirements that define the goals and best-practice policies to evolve the system using associative memory and event-driven interaction history to maintain stability and safety while achieving the system’s objectives. We demonstrate a structural machine, cognizing oracles, and knowledge structures derived from GTI used for designing, deploying, operating, and managing a distributed video streaming application with autopoietic self-regulation that maintains structural stability and communication among distributed components with shared knowledge while maintaining expected behaviors dictated by functional requirements. Full article

While a universal definition of religion eludes the field of religious studies, it certainty seems that people are becoming differently religious rather than a-religious, especially since the latter half of the twentieth century. To explain the enduring relevance of religion in human experience, this article expands on recent evolutionary and sociological research in the systems theory of religion and develops a philosophical approach to understanding religion as a complex adaptive system. Frameworks of meaning and beliefs communicated by religious systems emerge and adapt in relation to interpretive selection pressures communicated by individuals-in-community relative to entropy’s role in one’s contingent experience as a “teleodynamic self” in the arrow of time. Religious systems serve an entropy-reducing function in the minds of individuals, philosophically speaking, because their sign and symbol systems communicate an “anentropic” dimension to meaning that prevents uncertainty ad infinitum (e.g., maximum Shannon entropy) concerning matters of existential concern for phenomenological systems, i.e., persons. Religious systems will continue to evolve, and new religious movements will spontaneously emerge, as individuals find new ways to communicate their intuition of this anentropic dimension of meaning in relation to their experience of contingency in the arrow of time. Full article

Palliative care is dedicated to terminally ill patients with advanced disease, regardless of diagnosis, under the overarching premise of optimizing quality of life. This narrative review examines the extent to which principles of cybernetics and psychophysiology underlie this approach. Psychophysiology researches the physiological equivalents of psychological states and traits such as activation and individual reactivity, the interoception and the personal characteristics. Cybernetics specifies these principles, which are possible by understanding terms such as “psychophysiology” or “cybernetics” or “self-organization/autopoiesis”. The meaning of these terms for palliative care can also be elucidated in relation to the terms “biofeedback”, “consciousness”, “pain”, and “anxiety”. The common themes of cybernetics and psychophysiology are environment, subjectivity, personality characteristics, the difference between time scale separation in cybernetic systems, and real-time procedures in environment and rhythm. These lead to special therapies based on psychophysiology, such as consciousness training. The concepts of quality of life, causality, the biopsychosocial model, therapy, and autonomy are examined as palliative care concepts. The equivalents can be described from the perspective of cybernetics. For some palliative care-related terms, cybernetic thinking is already present (quality of life, autonomy, symptom control), while for others, it is not (biopsychosocial). Cybernetic terms (complexity, stability, identity, rhythm) are still used to a lesser extent in palliative care. Terms like genetic basis are common in cybernetics and psychophysiology to explain the identity of the subject in transition. Identity, on the other hand, is the basis of the concept of dignity in palliative care. Psychophysiology investigates disturbances like pain and psychological illnesses, which are also present in palliative care. Psychophysiology, cybernetics, and palliative care have subjectivity and resources in common. Therapies based on cybernetic principles of psychophysiology can also be used for symptom control in palliative care in the oncology setting. Full article

Ever since Varela and Maturana proposed the concept of autopoiesis as the minimal requirement for life, there has been a focus on cellular systems that erect topological boundaries to separate themselves from their surrounding environment. Here, we reconsider whether the existence of such a spatial boundary is strictly necessary for self-producing entities. This work presents a novel computational model of a minimal autopoietic system inspired by dendrites and molecular dynamic simulations in three-dimensional space. A series of simulation experiments where the metabolic pathways of a particular autocatalytic set are successively inhibited until autocatalytic entities that could be considered autopoietic are produced. These entities maintain their distinctness in an environment containing multiple identical instances of the entities without the existence of a topological boundary. This gives rise to the concept of a metabolic boundary which manifests as emergent self-selection criteria for the processes of self-production without any need for unique identifiers. However, the adoption of such a boundary comes at a cost, as these autopoietic entities are less suited to their simulated environment than their autocatalytic counterparts. Finally, this work showcases a generalized metabolism-centered approach to the study of autopoiesis that can be applied to both physical and abstract systems alike. Full article

This paper summarizes and reviews Chemical Organization Theory (COT), a formalism for the analysis of complex, self-organizing systems across multiple disciplines. Its elements are resources and reactions. A reaction maps a set of resources onto another set, thus representing an elementary process that transforms resources into new resources. Reaction networks self-organize into invariant subnetworks, called ‘organizations’, which are attractors of their dynamics. These are characterized by closure (no new resources are added) and self-maintenance (no existing resources are lost). Thus, they provide a simple model of autopoiesis: the organization persistently recreates its own components. The resilience of organizations in the face of perturbations depends on properties such as the size of their basin of attraction and the redundancy of their reaction pathways. Application domains of COT include the origin of life, systems biology, cognition, ecology, Gaia theory, sustainability, consciousness, and social systems. Full article