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Dr. Wolfgang Stegemann: Open Access Archive

Philosophy of Mind & Consciousness Theory

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From Autopoiesis to Enaction

Abstract: This paper reconstructs a conceptual shift from the original theory of autopoiesis to later enactive approaches to cognition and experience. The central claim is that the transition is not a straightforward deduction from autopoiesis. Maturana’s identification of life with cognition expands the concept of cognition from the outset. Later developments add embodied action, autonomy, adaptivity, agency, sense-making, and first-person experience. Each addition addresses a genuine problem, but the sequence risks turning biological regulation into semantic and eventually phenomenal vocabulary without identifying the mechanism that warrants the transition. The paper therefore distinguishes self-production, regulation, cognition, and experience as different explanatory targets. It argues that autopoiesis remains a powerful account of biological individuality if it is not equated with cognition. An alternative continuation is proposed: instead of locating the decisive development primarily in organism–environment coupling, the analysis follows the evolutionary differentiation of the living system itself, especially the emergence of nervous systems, fast signal integration, recursive closure, and a neurally constituted epistemic operational interior. Embodiment and environmental coupling remain necessary conditions, but they are not thereby mechanisms of experience. The result is a reconstruction of the historical divergence between autopoietic theory and later enactivism and a proposal for a biologically grounded route from living organization to cognition and phenomenal experience.

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A Thought Experiment on the In-Principle Impossibility of Constructed Consciousness

Abstract: The thought experiment is structured as a cascade. Each station formulates a thesis about what might give rise to experience. The thesis is tested against its strongest argument and rejected where it no longer explains experience adequately. Each failure gives rise to the next thesis. In this way, the question is driven progressively deeper, step by step. The conclusion holds on the condition that the requirements developed along this path are accepted. A precise question is being examined: Can consciousness be technically constructed, that is, can its constitutive organization be specified sufficiently and then deliberately realized? This must be distinguished from the question of whether technically created initial conditions could enable an open process in which life and, eventually, consciousness arise. This second possibility is not excluded from the outset. It must satisfy the same requirements as any other possible process of emergence.

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Why Artificial Life and Consciousness Are Impossible in Principle

Abstract: This essay develops an argument for the principled, not merely practical, impossibility of producing artificial life and artificial consciousness. The impossibility follows from the convergence of several lines of reasoning: from the nature of scientific abstraction, which always yields a map and never the landscape itself; from the size and branching structure of the evolutionary space of possibilities; from the active path-production of living systems, which continually co-produce their own space of possibilities rather than traversing a pre-given one; from the operative closure of biological autocatalysis, which shifts the concept away from the ahistorical, organizational reading of autopoiesis toward a historical-causal path thesis; and from the claim that ontology is the epistemic determination of the ontic, whereby the epistemic and ontological inaccessibility of the path collapse into one. The central aporia: construction presupposes a factorized description, yet what is causally relevant in the living is precisely its non-factorizability. The argument requires no assumption of a phenomenal residue separable from function and takes hold one step earlier, at the logical form of construction itself.

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From State to Mode: Criticality and Non-Factorizability as Constitutive Properties of Living Systems

Abstract: In earlier work, the phylogenetic sequence from autocatalytic autopoiesis through the causal core and electrification to defactorization was developed as a reconstructive derivation of the biological conditions of phenomenal consciousness. Non-factorizability appears there as the result of the fourth tipping point, criticality as its physical realization condition. The present article shows that both properties follow the same logic in the scaling sequence: they are present in autopoietic systems from the very beginning and develop qualitatively new forms with the scaling of the nervous system. This shared logic has remained implicit in previous work; making it explicit is the contribution of this article. The decisive difference from non-living dissipative systems lies in the fact that criticality there is a state a system has, whereas in autopoietic systems it is a mode in which the system operates as a living one. In the nervous system, this mode takes the specific form that realizes non-factorizability as a stable operating condition. The conceptual explanatory gain of this precision becomes apparent at two clinical phenomena: epilepsy and coma can no longer be understood as opposite points on an activation axis, but as structurally distinct failures of the same critical mode in opposite directions.

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The Biological Foundation of the Soul

Abstract: The soul has an image problem. Anyone who mentions it today in a scientific conversation can expect, at best, an indulgent smile. The concept is considered obsolete, a relic of a pre-scientific era in which whatever could not be explained was given a name, and the name was then mistaken for an explanation. And yet the question behind the concept never disappeared. What is it that makes an organism a subject? What is that inner point from which a being acts, perceives, and refers to itself? Science has not explained this point. It has circumvented it. Behaviorism declared inner states scientifically irrelevant: what counts is observable behavior. Cognitivism replaced the soul with information processing: the mind is a system, not a center. Freud operationalized it as the trinity of id, ego, and superego, psychologically precise but biologically unanchored. Modern neuroscience, finally, dissolved the center altogether: what remains are distributed networks, default mode networks, global workspaces, free energy. No place left for a soul. What all these movements have in common: they declared the inner center, the point of reference, either unscientific or dissolved it into functions, without asking whether something real might still lie behind the concept of the soul, something that merely needed a different description. Behaviorism forbade the question. Cognitivism reformulated it. Neuroscience dissolved it into networks. But forbidden, reformulated, and dissolved is not answered. David Chalmers captured this situation in a single phrase in 1995: the hard problem of consciousness. Why is there subjective experience at all? Why isn't it dark in there? Chalmers did not pose a new question; he named an old one that science had systematically circumvented. The hard problem is still considered unsolved today. This article proposes that it is not unsolved, but misconceived. The question “why is there experience?” presupposes that experience is something added to a physical system. The causal core shows that this presupposition is false.

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Neurally Driven Evolution: Behavior, Niche Construction, and the Acceleration of Variation Structure

Abstract: The nervous system invents no new evolutionary mechanism. It accelerates and complexifies an existing one. The first paper in this series showed that autocatalytic systems generate, through their history of perturbations, a structured variation space whose topology makes certain variations more probable than others. The present paper extends this thesis to the level of neural systems. The nervous system is not a fourth inheritance system in Jablonka's sense, but a possibility-space generator operating on a dramatically shortened timescale, which acts on the perturbation structure of offspring through niche construction, without leaving the causal architecture of the basic mechanism. Three empirically grounded channels connect neural processes to heritable variation structure: activity-dependent gene expression inscribed into the somatic genome of neurons; neuroendocrine axes transmitting chronic neural integration states to the germline; and niche construction as the primary indirect channel through which behavior shapes the perturbation environment of successive generations. The Weismann barrier remains intact throughout. The category error committed by Jablonka's behavioral inheritance system is avoided by maintaining strict causal-level distinctions.

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Perturbation, Integration, Possibility Space

Abstract: Neo-Darwinism describes the filter, not the structure of what gets filtered. It does not explain why highly adaptive phenomena occur: coherent, rapid adaptations across multiple traits simultaneously, which random search in the entire possibility space could not achieve. This paper develops an alternative framework. The central thesis is that autocatalytic systems generate, through their history of perturbations, a structured, non-uniformly distributed variation space whose topology makes certain variations more probable than others. When this pre-structured space is congruent with current selective pressure, the result appears highly adaptive. This congruence is neither guaranteed nor random, but itself a product of system history. The thesis is developed at the cell-biological, epigenetic, and evolutionary-biological levels, empirically anchored, and precisely demarcated from Jablonka's four-dimensions model and from neo-Darwinism. Recent findings on epigenetically driven mutational bias, stress-induced transposon mobilization, cryptic genetic variation, and the G-matrix framework provide converging empirical support.

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The Causal Core - A centralist principle of causality from the prokaryotic cell to self, ego, and agency

Abstract: This article develops the thesis that living systems form a centralist internal asymmetry from their very first appearance, a structure I refer to as the causal core. This core is not a morphological compartment and not a localisable site. It is a functional attractor that emerges from superposed thermodynamic flows within an operationally closed space, constitutes itself in the prokaryotic cell, and recurs in formally invariant fashion at every higher organisational level of the living. The article draws together the empirical evidence for this continuity from five domains, discusses five possible objections, and finally applies the model to self, ego, and agency. These three terms are not reconstructed as independent cognitive modules but as three descriptive directions of the same causal core at the highest level of biological complexity.

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The Placebo Effect as a Phenomenon of Autocatalytic Organization

Abstract: The standard neuroscientific account of the placebo effect identifies the neurochemical systems involved but fails to explain the constitutive transition from semantic context to physiological cascade. The dominant explanatory concept—expectation—does not resolve this gap; it merely relabels the explanandum. This paper proposes an alternative framework based on the theory of autocatalytic organization, drawing on the formal work of Rosen, Kauffman, and Montévil/Mossio. In an autocatalytically organized system, there is no translation between “meaning” and “physiology” because both are aspects of the same self-maintaining process. The placebo effect is reconceived as the integration of a perturbation into self-reinforcing cascades, governed by the topology of the autocatalytic network. This framework is applied to four empirical domains: psychoneuroimmunology (conditioned immunosuppression), open-label placebos, network neuroscience, and the placebome. Concrete, testable hypotheses are derived, including the prediction that perturbation-based measures of network non-factorizability should correlate with placebo magnitude. The clinical implications include a reframing of the drug–placebo distinction, a critique of the factorizability assumption underlying RCT design, and a rationale for individualized open-label placebo interventions.

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Experience as Self-Reference

Abstract: The present article advances a physical identity principle for consciousness: experience is not produced by, correlated with, or supervenient upon a specific class of physical states, it is identical with them. More precisely, experience is identical with endogenously generated, self-sustaining self-reference of the kind that autocatalytic systems necessarily instantiate when the infrastructure conditions identified in Stegemann (2026) are satisfied. This identity is not a contingent empirical finding but a conceptual one: the term ‘experience’ means nothing other than a physical state of the relevant structural type, described from the perspective of the system that is in it. The hard problem of consciousness, why physical processes give rise to subjective experience, is not solved by this principle but eliminated: the question rests on a false presupposition, namely that experience is something over and above the physical state. Once the presupposition is removed, no explanatory gap remains. The identity principle is stated in compact form as ℰ ≡ Πₐₙ, where ℰ denotes experience and Πₐₙ denotes the self-reference mapping of an autocatalytically organized system. The article distinguishes this structural identity thesis from classical type-identity theories, defends it against the multiple realizability objection and the knowledge argument, and draws out its consequences for the scientific study of consciousness.

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The Physical Infrastructure of Experience

Abstract: Contemporary theories of consciousness share a common methodological deficit: they describe functional correlates of experience without determining the structural conditions under which experience as such becomes possible at all. The present article develops a framework for the physical infrastructure of experience, the set of necessary structural conditions, not sufficient causal mechanisms, that a physical system must satisfy in order to make phenomenal experience possible. Drawing on the theory of causal collapse and the concept of the causal core as interpreter (Stegemann 2026a, 2025a, 2025b), the article argues that three mutually conditioning structural features constitute this infrastructure: (1) criticality, understood as the dynamic regime of phase transitions in which characteristic length scales diverge; (2) non-factorizability, understood as the ensuing impossibility of decomposing the causal structure of the system into independent partial causes; and (3) the causal core as a dynamic attractor in the system’s phase space, providing the reflexive dimension without which integrated causal unity would remain inert. Mathematically, three independent formal strands converge on the same structural situation: the Hammersley-Clifford theorem, the non-analyticity of the partition function, and the violation of the entanglement entropy area law, the last as a formal characterization tool, not a mechanistic hypothesis about neural quantum processes. An explicit demarcation from Integrated Information Theory shows that non-factorizability in the present framework is a categorical structural property, not a scalar measure. Comparison with superconducting coherence sharpens the anti-panpsychist argument, and concrete proposals for empirically distinguishing active from passive criticality are developed. The framework does not claim to solve the hard problem; it claims to determine the physical preconditions without which the hard problem cannot arise at all.

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The Causal Core as Interpreter

Abstract: Contemporary cognitive science operates predominantly with a representational paradigm that implies a linear causal structure: stimuli become neuronal patterns, these patterns "represent" world states, and subsequent processing stages operate on these representations. This conception misses the actual functioning of conscious systems. The present article develops an alternative conception: The causal nucleus (CC) interprets incoming neuronal patterns instead of processing them. This interpretation is done by non-linear interference between input patterns and the coherent system state of the KK. Mathematical formalization as phase-amplitude coupling shows that meaning does not lie in the patterns themselves, but arises from their non-factorizable interaction with the interpreting system state. This conception has far-reaching consequences for our understanding of perception, cognition and consciousness.

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A Framework for Consciousness: Autopoiesis, Causal Poiesis, Causal Collapse

Abstract: Where does consciousness come from? Despite numerous theories – from neuronal correlates to information processing to quantum physical hypotheses – this question remains unanswered if it is considered only within narrow disciplinary boundaries. This essay proposes an alternative approach: consciousness is not understood here as an emergent phenomenon or product of neuronal activity, but as the result of a multi-stage, systemic-thermodynamic process. The key concepts are: autopoiesis, causal poiesis and causal collapse. They mark three fundamental stages on which living systems emerge, center, and finally, under certain conditions, develop consciousness. The aim of this essay is to systematically reconstruct this path from life to consciousness on the basis of the concepts mentioned above – not in the sense of a goal-oriented development, but as a consequence of certain structural and exchange relations in open systems. This approach deliberately differs from established information-theoretical models such as Integrated Information Theory (IIT) or Global Neuronal Workspace Theory (GNWT). While these try to explain consciousness through functional information integration, the approach proposed here is based on structural-thermodynamic processes as they occur in the self-organization of living systems. Terms such as "causal core" or "causal collapse" are conceptual proposals that are based on concretely describable systemic properties – even if they have so far only been formalized and operationalized in initial theoretical work (cf. Stegemann, 2025a, 2025b). The present text is therefore not intended as a complete theory, but as a theoretical framework for the development of an interdisciplinary model of understanding.

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The mechanism of phenomenal experience

Abstract: The essay develops a reconstructive systems theory of consciousness based on the causal self-closure of biological systems. Consciousness is not understood as a property or effect, but as the epistemic form that inevitably arises when the causal structure of a system is completely self-contained. Physical, biological and phenomenal descriptions are epistemically autonomous forms of reconstruction that are structurally irreducible to each other. There is no translation relation between them, because they represent structurally heterogeneous modes of cognition within a single ontological basis. In contrast to functionalist theories, which presuppose consciousness by definition, this model reconstructs consciousness genealogically: from thermodynamic self-organization to biological autocatalysis to neuronal oscillation dynamics. The central thesis is that consciousness is not an emergent property of complex systems, but the epistemic form that a physical system necessarily assumes when its causal structure collapses completely into itself. For philosophers, this work shows why the hard problem is a category error: Physical and phenomenal description are different epistemic ways of reconstructing the same structure, not ontologically separated domains. For neuroscientists, it combines measurable correlates (oscillation dynamics, perturbational complexity index) with the necessity of subjective experience and explains why global integration implies an internal perspective.

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Methodology of Consciousness Theory

Abstract: Consciousness research suffers from a methodological and categorical double deficit. While the natural sciences explicitly discuss and justify their methods, consciousness research lacks systematic methodological reflection. This methodological deficit is functionally related to a basic categorical error: the confusion of epistemic levels of description with ontological entities. This level confusion results in three pseudo-problems, which are treated as central research questions, namely the body-soul problem, the hard problem and the what-is-it-like problem. The present article develops a reconstructionist method as a solution to this double deficit. This method avoids the categorical confusion between levels of description and ontology and identifies functional necessities instead of arbitrary correlations. Central is the insight that consciousness does not emerge from dead matter, but from autocatalytic organization. The model of causal collapse describes consciousness as a state of maximally non-factorizable causal entanglement in neuronal systems that arises when a measure of causal separability Σ(t) falls below a critical threshold Σc. The thesis systematically reconstructs the necessary conditions for consciousness: autocatalytic organization as a biological foundation, the causal nucleus as an evolutionary structural principle from the cell nucleus to the default mode network, electrical signal transduction in the nervous system, and finally causal collapse as a mechanism of phenomenal experience. Phylogenetic development shows how the causal nucleus as a structural principle permeates evolution from prokaryotes to early nervous systems to human consciousness. Different forms of consciousness are derived from specific collapse structures: primary consciousness as sensorimotor collapse, self-consciousness as recursive collapse with self-model, intentionality as prospective collapse, and affective consciousness as limbically integrated collapse. The theoretical positioning shows that the model integrates and specifies Integrated Information Theory, Global Workspace Theory and plasticity approaches. Empirically, the model is supported by the Perturbational Complexity Index (PCI), functional connectivity patterns, and characteristic differences between states of consciousness. For predictions that are not directly proven, concrete test procedures are proposed. The method transforms arbitrary correlations into functional necessities and opens up new avenues for empirical research, artificial systems of consciousness and clinical applications.

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Cognitive Surplus Capacity as the Foundation of Cultural Construction

Abstract: This article develops the thesis that the major cultural constructions of humanity (religion, esotericism, art, science) result from a structural discrepancy between cognitive processing capacity and available sensory inputs. While cognitive systems with low neural complexity can operate largely reactively to sensory data, significant surplus capacity necessitates constructive processing beyond the given. These constructions differ not in their cognitive source, but in their methodological constraints: religion dogmatizes its constructions, art makes them explicit as such, science organizes them under conditions of falsifiability. The thesis is developed as a heuristic principle that makes disparate cultural phenomena comprehensible under a unified perspective and is categorially specified to avoid confusions between structural, functional, and phenomenal levels of description.

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Consciousness as a collapse of causality

Abstract: Why do we feel something? Why is there not only motion, reaction and calculation in a part of the universe, but also experience, qualia, self-awareness? Classical physics knows only cause and effect, computer science only knows input and output. But in consciousness, both seem to blur. This essay is based on the thesis: Consciousness arises where a recursive causal system loses the distinction between cause and effect of its own states. Based on concepts such as autocatalysis, information density, feedback and self-reference, we develop an interdisciplinary model of sensing – between physics, philosophy and artificial intelligence. 

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Consciousness as an Expression of Autocatalytic Stability – A New Index for Neuronal Coherence

Abstract: The present model assumes that consciousness is not an additive effect of cognitive complexity, but a specific form of systemic integration: a “causal collapse” within the space of recursive processes. This term does not mean destruction, but a temporary indistinguishability of causal paths – a state in which stimulus processing, memory retrieval, and self-modeling can no longer be separated. This collapse is not purely functional, but a structural-energetic phenomenon: It only arises when a system maintains its autocatalytic stability, i.e., when feedback processes are recursively stabilized within a critical range. Such stabilization can only occur in living systems – those that not only consume energy but also regulate it cyclically.

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From the Transcendental Subject to the Causal Core

Abstract: The relationship between subject and object has been the crystallization point of consciousness research since transcendental philosophy. From Kant to Husserl, attempts were made to understand the conditions of the possibility of knowledge from the structure of the subject. However, with the transition to empirical neuroscience, this question has not disappeared, but has merely been transformed. The transcendental framework continues to have an effect – as an implicit prerequisite of many theories that see themselves as naturalistic. The present text pursues the goal of making this implicit framework visible and overcoming it. He traces the historical development from transcendental philosophy to today's neuro- and systems-theoretical models of consciousness, in order to finally propose an alternative concept: that of causal collapse and the causal core. These terms do not describe consciousness as an emergent product, but as a structural consequence of the self-binding of causal processes. In this way, the classic pair of opposites of spirit and nature is abolished without falling into reductionism.

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Models and the test of consciousness

Abstract: For decades, new theories have been emerging that want to explain what consciousness is. They speak of information integration (Tononi, 2004, 2015), of global availability (Baars, 1988; Dehaene, 2014), recursive predictions (Friston, 2010) or phenomenological structures (Varela, Thompson & Rosch, 1991). Their common conviction is that consciousness can be explained by certain dynamics and forms of organization. But the crucial question remains: How could we tell that such a model not only sounds conclusive, but actually produces consciousness? In the following, it will be shown that all current models of consciousness are subject to a fundamental test. Four aspects must be considered: (1) its generative power, which has not yet been proven, (2) its metaphysical positions, (3) its circular validation between theory and empiricism, and (4) its predominantly interpretive, non-explanatory function.

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Category errors as a structural principle of philosophy

Abstract: This paper identifies and analyzes systematic category mistakes that pervade classical and contemporary philosophical debates from antiquity to the present, structuring discussions in ontology, epistemology, philosophy of mind, and ethics. Six fundamental types of category errors are distinguished: ambiguity of central concepts; conflation of descriptive levels; substantive reification of processes; confusion of syntax with semantics; ungrounded metaphysical assumptions; and ontologization of normative values. Through classical and modern examples, it shows how unmarked shifts between logical levels generate theoretical confusion, misleading metaphysical claims, and conceptual puzzles. The diagnosis reveals that many current scientific and philosophical theories revive old category errors in new forms under the guise of exact sciences, particularly in cognitive science, artificial intelligence, and neuroscience. The paper argues for establishing "category hygiene" as a methodological principle that clarifies conceptual distinctions, avoids illegitimate ontological claims, and grounds philosophy more firmly in critical reflection and empirical engagement. This approach aims to revitalize philosophy's critical role by dispelling persistent confusions rather than generating novel metaphysical systems.

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The Causal Core as a Structural Principle of Free Will

Abstract: The debate on free will remains shaped by metaphysical speculation, reductionist simplifications, and categorical misunderstandings. While classical philosophy often conceived it as a gift of divine grace or the expression of rational autonomy, modern neuroscience and cognitive models tend to deny freedom in favor of deterministic or probabilistic causal chains. This article advances the thesis that the capacity for intentional action is not rooted in an immaterial will, but in a structural center that emerged in the course of biological evolution: the causal core. This core is not a substance but a dynamically integrating system function, thermodynamically initiated, biologically centered, and psychologically accessible. Drawing on thermodynamic principles, the theory of autopoiesis, and system theory, the article traces the causal core’s genesis from autocatalytic chemical cycles and the encapsulation of protocells, through the emergence of the eukaryotic cell nucleus as a morphologically identifiable locus, to its complex integration in neural systems. The causal core stabilizes selective coupling and enables intentional, goal-oriented behavior. By distinguishing biological and psychological levels of description and avoiding the category error of causal reductionism, the article proposes a consistent systems-theoretical model that unites empirical findings with a coherent epistemological framework. The implications for the concept of free will are discussed, along with applications to artificial systems and animal cognition.

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Valence as a universal principle of binding and weighting

Abstract: This work develops a unified theory of valence as a scale-spanning organizational principle from quantum chemistry to political ideology. Valence is defined as preferential stabilization - a mechanism that begins with energetic preferences in chemical bonds and continues through biochemical affinities and neuromodulatory signaling to cognitive evaluation processes. The central thesis states that ideological beliefs emerge and are stabilized through the same valence-based weighting mechanisms that modulate synaptic plasticity. This perspective explains the persistence and rigidity of political worldviews as natural consequences of neurochemical reinforcement systems, not as cognitive defects. The theory generates testable predictions for pharmacological, psychophysiological, and neuroimaging studies and has implications for therapeutic interventions in ideological rigidity as well as for the design of democratic institutions. In contrast to rationalistic approaches, valence theory emphasizes the fundamental role of emotional evaluation in all human cognition, offering a naturalistic alternative to normative ideals of rational discourse.

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Physics of Organismic Storage

Abstract: Current neuroscientific models of memory usually view memory as a function, for example as a reactivation of earlier activation patterns, as a symbolic encoding, or as the recognition of stored content. In this perspective, memory is primarily understood as a functional change in state or as the re-availability of semantic or sensory information that is stabilized by synaptic plasticity or molecular modulation. What is usually missing is a physically sound description of what "storage" actually means. In the position represented here, therefore, a radical change of perspective is undertaken: memory is not the reappearance of a stored symbol, but the material, directed restructuring of the system itself. In this sense, memory is not a passive archive, but the active expression of a structural transformation. Storing means that a system has changed irreversibly – and this change is not metaphorical, but physically real.

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Consciousness: An Integrative Model of the Four Fundamental Principles

Abstract: Consciousness is defined as the emergent state of a system that fulfills four fundamental principles: (1) autocatalysis as the energetic basis of self-sustaining processes, (2) a causal core as a thermodynamically determined integration center, (3) causal collapse as the fusion of separate causal pathways into an irreducible entity, and (4) plasticity as structural adaptability. The model differs from existing theories in its process-ontological approach: consciousness does not arise through information processing or representation, but through the physical fusion of causal processes. This theory makes specific, empirically testable predictions about neuronal correlates of consciousness and offers new explanatory approaches for pathological states of consciousness, animal consciousness and the limits of artificial intelligence.

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Epistemology & Logic

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The Invariance Trap

Abstract: Philosophical fallacies arise not only from false premises or ambiguous words. They can also arise when an expression, a function, a structure, or a description is transferred from one context to another. In such transformations, something is typically preserved while something else changes. This paper calls a property invariant relative to a particular transformation when it is preserved across that transition. Depending on the case, what remains invariant may be a linguistic expression, a semantic function, a material structure, a formal relation, or some other feature. The central error occurs when the preservation of one dimension is taken, without independent justification, to establish the preservation of another. This is termed unwarranted invariance transfer. The approach is developed through six types of transformation: expression and meaning, semantic function and causal realization, levels of description, perspectives of attribution, model and object, and metaphorical transfer. The analysis does not claim that every such case is a category mistake in Ryle's classical sense. Rather, it identifies a general inferential form through which equivocations, level confusions, category mistakes, and unwarranted ontological attributions can arise. Functionalism, the Free Energy Principle, and Integrated Information Theory serve as critical test cases for locating the burden of justification and analyzing concrete invariance errors.

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From Autopoiesis to Enaction

Abstract: This paper reconstructs a conceptual shift from the original theory of autopoiesis to later enactive approaches to cognition and experience. The central claim is that the transition is not a straightforward deduction from autopoiesis. Maturana’s identification of life with cognition expands the concept of cognition from the outset. Later developments add embodied action, autonomy, adaptivity, agency, sense-making, and first-person experience. Each addition addresses a genuine problem, but the sequence risks turning biological regulation into semantic and eventually phenomenal vocabulary without identifying the mechanism that warrants the transition. The paper therefore distinguishes self-production, regulation, cognition, and experience as different explanatory targets. It argues that autopoiesis remains a powerful account of biological individuality if it is not equated with cognition. An alternative continuation is proposed: instead of locating the decisive development primarily in organism–environment coupling, the analysis follows the evolutionary differentiation of the living system itself, especially the emergence of nervous systems, fast signal integration, recursive closure, and a neurally constituted epistemic operational interior. Embodiment and environmental coupling remain necessary conditions, but they are not thereby mechanisms of experience. The result is a reconstruction of the historical divergence between autopoietic theory and later enactivism and a proposal for a biologically grounded route from living organization to cognition and phenomenal experience.

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Association, Relation, and Category Errors

Abstract: Four-dimensional logic distinguishes four epistemic dimensions of thought: D1 as immediate and reactive linking, D2 as systematic and rule-guided relation formation, D3 as reflexive examination of the rules and categories employed, and D4 as the contextual and perspectival determination of their validity. The present paper extends this approach by developing a theory of relation formation. It starts from the assumption that thinking consists, at an elementary level, in registering differences and establishing connections. The character of these connections changes, however, with the epistemic dimension. D1 generates associations, D2 specifies relations, D3 examines their categorial and metatheoretical presuppositions, and D4 determines the context while also marking the chosen standpoint as perspectival. This yields a systematic account of a widespread error in scientific and philosophical reasoning: an initially justified association is upgraded at D2 into a strong relation without D3 examining the relevant levels of description or D4 examining the context of validity. To capture this error formally, a level operator is introduced that assigns each expression to a level of description. Relations additionally receive a signature defined as a set of admissible pairs of levels. An unmarked transfer of a relation to terms belonging to other levels of description thereby becomes visible as an unjustified relation transfer. Using functionalism as a further example, the paper shows that partial functional equivalence does not entail phenomenal equivalence unless an independent bridge premise is justified. A strong functionalism can formulate such a bridge as a claim of sufficiency or identity, but thereby shifts the burden of justification to D3. The extension remains compatible with the existing framework of dimensional logic because it introduces neither new truth values nor new ontological layers. Rather, it sharpens the epistemic control of relations and makes visible how plausible connections can develop into category errors.

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The Functionalist Trilemma

Abstract: Functionalism is among the most influential positions in the philosophy of mind. Its central idea is that mental states are determined not by their material constitution but by their functional or causal role. This gives rise to the possibility of multiple realization: if the same functional organization can be realized in biological and artificial systems, then, in principle, the same mental states should also be possible in different material substrates. This paper argues that this inference does not hold for phenomenal consciousness. Functional equivalence initially establishes equivalence only with respect to functionally specified properties. For phenomenal equivalence to follow, an additional bridge premise is required according to which a particular functional organization is sufficient for experience. There are three argumentative possibilities for such a bridge. It may be stipulated definitionally, justified as an empirical generalization, or asserted as a fundamental psychophysical principle, for example as a necessary identity or a fundamental law. In the first case, consciousness is not explained but functionally redefined. In the second case, empirical evidence from biological systems is insufficient to establish substrate independence. In the third case, the transition from function to experience is carried by an additional principle rather than by the functional description itself. This problem can be formalized as a factorization problem. A functional description is an abstraction that maps different realizations onto the same functional class. Functionalism about consciousness additionally claims that experience factors through precisely this abstraction, and therefore remains invariant within every functional equivalence class. This invariance does not follow from the abstraction itself. It is the central additional assumption of functionalism. Functionalism can therefore describe functional equivalence, but it cannot derive phenomenal equivalence from functional equivalence alone.

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Dimensional Transition Logic

Abstract: An earlier draft of dimensional logic introduced four epistemic dimensions into the formal syntax and postulated transition operators between them, but left these operators substantively undetermined. They had names and a notation, yet no specification of what they compute. The present article closes this gap for the central transition. It determines the step from the systematic to the reflexive level as quotient formation under a chosen equivalence relation and derives, for weaker relations, a degree of coherence that measures the formal rigor of the abstraction and is calculated rather than stipulated. This degree of coherence must be distinguished from the object related adequacy of an aspect. The transition to the highest level proves to be of a different kind. It is not a further abstraction, but the relinquishment of a privileged aspect. What follows is not an additional degree of truth, but a perspectival validity profile over the space of admissible aspects. Dimensional logic thereby acquires, for the first time, determinate transitions whose formal properties can be checked, together with a criterion that distinguishes the reflexive level from the relativizing one.

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A Thought Experiment on the In-Principle Impossibility of Constructed Consciousness

Abstract: The thought experiment is structured as a cascade. Each station formulates a thesis about what might give rise to experience. The thesis is tested against its strongest argument and rejected where it no longer explains experience adequately. Each failure gives rise to the next thesis. In this way, the question is driven progressively deeper, step by step. The conclusion holds on the condition that the requirements developed along this path are accepted. A precise question is being examined: Can consciousness be technically constructed, that is, can its constitutive organization be specified sufficiently and then deliberately realized? This must be distinguished from the question of whether technically created initial conditions could enable an open process in which life and, eventually, consciousness arise. This second possibility is not excluded from the outset. It must satisfy the same requirements as any other possible process of emergence.

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Dimensional Logic - Basics, Structure and Applications

Abstract: This article proposes a novel logical framework—dimensional logic—that extends classical two-valued logic into a stratified system of epistemic modalities. Based on four cognitive abstraction layers (D1–D4), it captures differentiated modes of thinking: from direct perception (D1) to formal reasoning (D2), epistemic self-reflection (D3), and contextual integration (D4). These dimensions are formalized through transformation operators and axioms governing consistency, projection, and emergent properties. The logic is applied to paradoxes, decision problems, and mathematical modeling to demonstrate how dimensional analysis can resolve contradictions and enhance interpretability. The proposed system integrates logical rigor with contextual sensitivity, making it suitable for modeling complex cognitive, ethical, and artificial systems. It also opens pathways for rethinking the foundations of logic, particularly in situations involving self-reference, emergence, and epistemic framing.

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The Operator That Cannot Place Itself

Abstract: Friedrich Heinrich Jacobi's 1787 objection to Kant's transcendental idealism identified a structural problem that remains unresolved in the tradition of nested ontological frameworks: any system that posits causal relations between distinct ontological levels requires an operator to mediate those relations, but this operator cannot itself be ontologically located without generating an infinite regress. We argue that this problem is not peripheral to Kant's system but constitutive of it, and that its modern descendants, including layered ontologies of mind and body, hierarchical emergence theories, and multi-level realist frameworks, inherit the same defect. We further argue that the problem dissolves, rather than is solved, once the assumption generating it is abandoned: the assumption that ontological levels are real strata rather than epistemic modes of access to a single physical reality. Drawing on the perspectival entity ontology and dimensional logic developed in prior work (Stegemann 2026a, 2026b, 2026c), we show that replacing causal inter-level operators with reflexive epistemic operators eliminates the regress, preserves scientific realism, and reframes classical puzzles, including the Hard Problem of Consciousness and the measurement problem in quantum mechanics, as dimensional category errors rather than metaphysical mysteries.

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Dimensional Logic as a Formal Inference System

Abstract: Classical predicate logic operates under the assumption of dimensional homogeneity: statements are evaluated as either true or false, regardless of their epistemic context or the cognitive level at which they operate. This article develops a systematic extension of symbolic logic that removes this limitation. Dimensional logic introduces explicit epistemic dimensions into formal syntax, relativizes the truth predicate to multidimensional profiles, and establishes transition rules between different levels of knowledge. The resulting system retains the advantages of classical logic within the systematic dimension, while formally integrating immediate perception, reflexive metacognition, and contextual embedding. We use detailed examples (prisoner's dilemma with concrete parameters, ethical decisions, scientific statements) to show that this extended system can formally distinguish categorically different modes of validity and thus make category errors detectable as formal violations.

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Perspective Ontology and Dimensional Logic

Abstract: The present work develops an ontological foundation for dimensional logic (Stegemann, 2025a) that goes beyond its formal architecture. The starting point is a critique of Kant's concept of the thing-in-itself, which is rejected as a substance-realistic stage metaphor. In its place is a perspectival entity ontology: each entity constitutes its world through its own structural properties; there is no reality transcendent beyond these constitutional achievements. This position is shown as an epistemic-ontological circle, which is not considered an error in thinking, but a constitutive feature of finite existence. Against this background, dimensional logic appears as a species-specific coordinate system of human world order, a system that explicitly formalizes its own perspectivity as a fourth dimension and is thus more consistent than systems that make a species-neutral claim to universality without naming their own point of view. The article situates this position in relation to Kant, Leibniz, Nietzsche, Uexküll, Maturana/Varela, Whitehead and Heidegger and elaborates on both kinship and decisive differences.

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Beyond Gödelian Limits

Abstract: Gödel's incompleteness theorems demonstrate fundamental limitations of formal systems: no sufficiently powerful consistent system can prove its own consistency. This insight is often interpreted as limiting all forms of systematic self-reference. This article develops an alternative perspective by introducing a dimensional epistemology that distinguishes between different modes of cognitive processing. It is argued that Gödel's results pertain specifically to formal self-reference (Dimension 2), while reflexive metacognition (Dimension 3) represents a categorially different form of self-relation not subject to the same constraints. Reflexivity is understood not as a theorem within a formal system, but as a perspectival access to that system. This distinction has far-reaching consequences for debates about artificial intelligence, theories of consciousness, and the limits of formalizability.

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From 2D Object Space to 3D Perspective Structure

Abstract: This paper addresses the structural conditions under which objectivity can emerge when multiple perspectives are present. Standard approaches typically presuppose a shared object space and treat differences between observers as secondary deviations. This working paper suspends that assumption and formalizes the transition from a two-dimensional object space to a three-dimensional perspective structure. The formalization introduces a perspective group that acts on objects, allowing perspective-invariant comparison through alignment operations. This mathematical framework generates operators for reflexivity and contextual coherence without requiring external assumptions. The extension from D2 (systematic comparison) to D3 (perspectival alignment) and D4 (contextual integration) provides a dimensional logic that stabilizes cooperation in rational decision-making. This compact technical paper demonstrates the core mechanism of dimensional logic through a specific application: perspective alignment in cooperation problems. It serves as the formal foundation for the framework developed in "Adaptive Rationality through Dimensional Logic" (Stegemann, 2025) and illustrates how perspective-invariant metrics can be operationalized in decision architectures. 

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Dimensional Mathematics: An Axiomatic Extension of Epistemic Relativity

Abstract: This record contains two complementary files: Article (PDF): Dimensional Mathematics Application – A theoretical exposition of dimensional logic and its application to the Prisoner’s Dilemma. The paper develops the formal operators σ₂ (systematic derivation), μ₃ (reflexivity), and κ₄ (contextual coherence), and demonstrates how these extend classical game theory by integrating epistemic relativity. Python Code (.py): A simulation script implementing the dimensionally extended Prisoner’s Dilemma. It allows users to explore the modified utility functionUC=R+α⋅Δμ+β⋅Δκ(θ)U_C = R + α \cdot Δμ + β \cdot Δκ(θ)UC=R+α⋅Δμ+β⋅Δκ(θ)and test conditions under which cooperation becomes a rationally stable equilibrium. Together, the article and the code provide both a conceptual foundation and a computational tool for exploring epistemically extended rationality in game-theoretic contexts.

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Dimensional Logic - Basics, Structure and Applications

Abstract: This article proposes a novel logical framework—dimensional logic—that extends classical two-valued logic into a stratified system of epistemic modalities. Based on four cognitive abstraction layers (D1–D4), it captures differentiated modes of thinking: from direct perception (D1) to formal reasoning (D2), contextual integration (D3), and epistemic self-reflection (D4). These dimensions are formalized through transformation operators and axioms governing consistency, projection, and emergent properties. The logic is applied to paradoxes, decision problems, and mathematical modeling to demonstrate how dimensional analysis can resolve contradictions and enhance interpretability. The proposed system integrates logical rigor with contextual sensitivity, making it suitable for modeling complex cognitive, ethical, and artificial systems. It also opens pathways for rethinking the foundations of logic, particularly in situations involving self-reference, emergence, and epistemic framing.

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AI Critique & ALI Model

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The Functionalist Trilemma

Abstract: Functionalism is among the most influential positions in the philosophy of mind. Its central idea is that mental states are determined not by their material constitution but by their functional or causal role. This gives rise to the possibility of multiple realization: if the same functional organization can be realized in biological and artificial systems, then, in principle, the same mental states should also be possible in different material substrates. This paper argues that this inference does not hold for phenomenal consciousness. Functional equivalence initially establishes equivalence only with respect to functionally specified properties. For phenomenal equivalence to follow, an additional bridge premise is required according to which a particular functional organization is sufficient for experience. There are three argumentative possibilities for such a bridge. It may be stipulated definitionally, justified as an empirical generalization, or asserted as a fundamental psychophysical principle, for example as a necessary identity or a fundamental law. In the first case, consciousness is not explained but functionally redefined. In the second case, empirical evidence from biological systems is insufficient to establish substrate independence. In the third case, the transition from function to experience is carried by an additional principle rather than by the functional description itself. This problem can be formalized as a factorization problem. A functional description is an abstraction that maps different realizations onto the same functional class. Functionalism about consciousness additionally claims that experience factors through precisely this abstraction, and therefore remains invariant within every functional equivalence class. This invariance does not follow from the abstraction itself. It is the central additional assumption of functionalism. Functionalism can therefore describe functional equivalence, but it cannot derive phenomenal equivalence from functional equivalence alone.

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ALI: A Bounded Architecture for Controllable Autonomous Agents

Abstract: Autonomous agents operating over extended periods face requirements that are qualitatively different from those of isolated task execution. A system that must continuously preserve operational integrity while generating and evaluating behaviour cannot be organised around a single reasoning process without sacrificing transparency and controllability. We present Artificial Local Intelligence (ALI), a reference architecture that decomposes autonomous operation into five explicitly separated responsibilities: a Causal Core that evaluates operational viability before planning begins, an Ego that generates behavioural proposals without evaluating them, a Super-Ego that evaluates proposals without generating them, a Memory that preserves every decision as a complete and immutable operational episode, and a Runtime that coordinates the cycle without participating in reasoning. We provide a complete architectural specification, a compliance criteria set of 44 verifiable SHALL requirements, and an open-source reference implementation in Python that requires no third-party dependencies. The implementation is verified by 72 automated tests and includes a plugin system that allows any architectural component to be replaced through configuration. A comparison against BDI architectures, SOAR, LangGraph, and the Microsoft Agent Framework shows that no existing production framework provides an independent architectural component for operational viability monitoring or enforces the separation of behavioural generation from normative evaluation at the architectural level.

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Beyond AGI: The Case for Artificial Local Intelligence

Abstract: Artificial General Intelligence, or AGI, means something different to everyone. The one thing most definitions share is the word general: an intelligence without a fixed domain, capable of anything a human can do. This generality is the wrong goal for the autonomous systems. The robot that inspects an offshore wind turbine does not need general intelligence. The monitoring system that maintains a server cluster does not need to write poetry. The autonomous agent that manages a production process does not need a theory of mind. What these systems need is a clear architecture, a defined scope of action, and a principled basis for autonomous behavior. That is what Artificial Local Intelligence, or ALI, provides.

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Four-Dimensional Decision Stability: Integrating Dimensional Logic into the ALI Architecture

Abstract: We extend the ALI architecture by integrating Dimensional Logic (Stegemann 2025), a framework in which truth is defined as a fixpoint across four cognitive dimensions: reactive (D1), systematic (D2), reflexive (D3), and contextual (D4). The ALI is uniquely built bottom-up: its founding principle is not a task but the operative self-preservation principle of the causal core, derived from autocatalytic biology. Controllability, task execution, and normative constraint are not restrictions imposed on a capable system, they are consequences of the founding principle. This distinguishes the ALI from all top-down approaches that add safety constraints after capability specification. The first three dimensions correspond directly to the established ALI instances, causal core (CC), Ego, and Super-Ego, while D4 constitutes a new fourth component: the Kontext-Modulator, a read channel that informs the Super-Ego of external deployment signals without writing to the normative structure. In the ALI, the logical, cognitive, and epistemic aspects of Dimensional Logic collapse into a single layer because the absence of causal collapse eliminates the phenomenal gap that separates these aspects in conscious agents. D4 is the only channel through which information enters the ALI that is not fully formalised at entry. Every decision is classified by its fixpoint score (1/4 to 4/4): the degree to which it satisfies all four dimensions simultaneously. Simulation results show 100% decision stability (4/4 fixpoint score) across all context phases. Controllability is maintained throughout: the Super-Ego retains veto power; the Kontext-Modulator informs but does not override normative structure. Stage 10 concludes the ALI simulation series.

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Artificial Local Intelligence: Architecture and Reference Implementation

Abstract: Autonomous agents operating over extended periods face requirements that are qualitatively different from those of isolated task execution. A system that must continuously preserve operational integrity while generating and evaluating behaviour cannot be organised around a single reasoning process without sacrificing transparency and controllability. We present Artificial Local Intelligence (ALI), a reference architecture that decomposes autonomous operation into five explicitly separated responsibilities: a Causal Core that evaluates operational viability before planning begins, an Ego that generates behavioural proposals without evaluating them, a Super-Ego that evaluates proposals without generating them, a Memory that preserves every decision as a complete and immutable operational episode, and a Runtime that coordinates the cycle without participating in reasoning. We provide a complete architectural specification, a compliance criteria set of 44 verifiable SHALL requirements, and an open-source reference implementation in Python that requires no third-party dependencies. The implementation is verified by 72 automated tests and includes a plugin system that allows any architectural component to be replaced through configuration. A comparison against BDI architectures, SOAR, LangGraph, and the Microsoft Agent Framework shows that no existing production framework provides an independent architectural component for operational viability monitoring or enforces the separation of behavioural generation from normative evaluation at the architectural level.

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drwolfgangstegemann-sudo/ali-reference-implementation: ALI Reference Implementation v0.4

Abstract: No description provided.

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Artificial Local Intelligence: Architecture and Reference Implementation

Abstract: This book presents the complete architectural specification of Artificial Local Intelligence (ALI), a reference architecture for autonomous agents that separates five organisational responsibilities into independent components: a Causal Core for operational viability assessment, an Ego for behavioural generation, a Super-Ego for normative evaluation, a Memory for historical continuity, and a Runtime for execution coordination. The specification comprises 24 chapters covering design principles, component descriptions, the operational cycle, learning, architectural stability, and controllability, together with 10 appendices including a formal compliance specification of 44 verifiable SHALL requirements, a complete API specification, a configuration reference, and an architectural data model. The open-source reference implementation is available at: https://github.com/drwolfgangstegemann-sudo/ali-reference-implementation

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Second-Order Meta-Learning and Factorizability: The Boundary Between State and History in the ALI Architecture

Abstract: We introduce second-order meta-learning into the ALI architecture: the accommodation threshold theta adapts based on the effectiveness history of past accommodations, making the system learn when it learns. A factorizability test measures divergence between the original agent and a clone initialised from an identical state snapshot but without the effectiveness history. Over 5000 training episodes, theta rises monotonically from 15 to 40 (its ceiling) in 13 upward steps and zero downward steps. Factorizability divergence remains at 0.0 throughout. We interpret this result as a precise localisation of the factorizability boundary: single-parameter second-order meta-learning converges to a fixed point when the environment produces consistently fast accommodation redundancy. At a fixed point, the effectiveness history is irrelevant, factorizability is maintained, and historical constitution does not arise. The hypothesis that second-order meta-learning destroys factorizability is neither confirmed nor falsified: it is refined. Historical constitution requires persistent meta-learning dynamics without a fixed point, which in turn requires environmental heterogeneity in accommodation effectiveness. This finding concludes the simulation series and defines the conditions under which ALI deployment could approach the factorizability boundary.

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Assimilation and Accommodation in the ALI Super-Ego: A Piagetian Model of Norm Development

Abstract: We extend the adaptive Super-Ego of Stage 7 with a Piagetian norm development mechanism: assimilation handles perturbations that fit existing norms by adjusting weights; accommodation generates new norms from recurring norm-gaps that cannot be assimilated. Over 5000 training episodes, 10 accommodation events occur, all generating the same norm type (force-eat-search: block non-eating actions when energy is critical and no packet is underfoot). The central finding is a dynamic competition between accommodation and assimilation: the Ego's Q-learning independently closes the same norm-gap that the Super-Ego is accommodating, rendering the accommodated norms behaviorally redundant as learning progresses. The assimilation-accommodation boundary is not fixed but shifts with Ego learning maturity. By episode 5000, P1 norm-gap events have declined from 118 per interval to 12 total, survival reaches 96.6%, and base norm weights converge to their maximum (3.0) as in Stage 7. The accommodation mechanism produces structurally valid norms that respect the CC integrity condition, but their functional relevance decreases as the Ego's own learning achieves what the Super-Ego was normalising. This mirrors Piaget's observation that accommodated schemas can become redundant when more general assimilation schemas develop, and establishes a formal parallel between cognitive equilibration and normative equilibration in multi-instance ALI architectures.

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Norm Sensitisation Under Meta-Learning: Adaptive Super-Ego Weights in the ALI Architecture

Abstract: We introduce adaptive Super-Ego norm weights into the ALI architecture, implementing a hierarchical learning Super-Ego (Option B) in which individual norm weights evolve based on activation frequency and causal core (CC) stability, governed by static meta-norms M1-M3. Over 4000 training episodes with a Q-learning Ego and a two-dimensional CC, all three tested norms (N1: no poison, N3: no delivery below energy threshold, N7: no movement below integrity threshold) converge to their maximum weight ceiling (3.0) within 1500 episodes and remain there for the remainder of training. This convergence occurs through the norm sensitisation pathway: a norm that is rarely or never activated has its weight increased, because its low activation indicates successful internalisation by the Ego rather than irrelevance. The central finding is that norm weight learning in a well-functioning ALI system produces sensitisation, not erosion. A normative architecture that is behaviorally effective renders its own norms less frequently triggered, and the meta-learning rule responds by strengthening those norms further. This is the opposite of the erosion dynamic that critics of adaptive normative systems typically fear. The result directly addresses the concern, raised in recent public debate, that a learning Ego undermines the controllability of the Super-Ego: under the tested architecture, learning in the Ego stabilises and strengthens the normative layer rather than eroding it.

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Learning to Preserve: Q-Learning in the Two-Dimensional Causal Core Framework — Reward Attribution, Dual Crisis Prevention, and the Emergence of Conservative Self-Preservation Strategies

Abstract: We combine the Q-learning Ego of Stage 4 with the two-dimensional causal core (CC) of Stage 5, creating a learning agent that balances energy and structural integrity through an internally derived reward signal without any external specification. The training process reveals a reward attribution failure: an implementation error that assigned the collection reward regardless of collection success produced a stable but fully dysfunctional strategy over 3000 episodes, with reward growing to +23 per episode while deliveries remained at zero. After correction, the agent converges to a viable strategy over 4000 episodes, achieving 100% survival across 20 test seeds compared to 0% for the hardcoded Stage 5 Ego over the same episode length. The central finding is a strategic inversion: instead of replicating the explicit priority ordering of the hardcoded Ego, the Q-learning Ego discovers a preventive strategy that avoids dual crisis entirely through proactive rest allocation, using 54.8 rest actions per run compared to 13 in Stage 5. Zero dual crisis events occur across all 20 test seeds. Mean delivery performance drops to 0.35 per run compared to approximately 4.0 for the hardcoded Ego. The same CC reward signal thus generates two qualitatively different behavioral equilibria: a task-execution equilibrium with reactive integrity management, and a survival equilibrium with preventive integrity management. Norm N7 is never activated, confirming that preventive norm compliance emerges from CC-evaluated Q-learning as reliably as from explicit priority ordering. These findings establish that the CC metric does not uniquely determine behavioral strategy, and that explicit constraints remain necessary to select the deployment-relevant equilibrium among multiple viable ones.

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The Multi-Dimensional Causal Core: Energy and Structural Integrity as Competing Self-Preservation Dimensions in ALI

Abstract: We extend the causal core (CC) of the ALI simulation from a scalar energy value to a two-dimensional integrity vector comprising energy and structural integrity. Both dimensions are genuine self-preservation parameters: energy governs metabolic continuity, structural integrity governs the mechanical capacity for action. Movement and collection incur wear on structural integrity; rest at the delivery station repairs it. Over 900 parameterised runs across five wear rates, three repair rates, and three resource density levels, we document four central findings. First, dual crisis — simultaneous criticality of both CC dimensions — occurs in 93% of all runs, establishing that the two-dimensional CC generates conflict situations structurally absent from the one-dimensional model. Second, shutdown is caused by energy depletion in 100% of cases, never by integrity failure, revealing an asymmetric controllability between the two CC dimensions: integrity is internally controllable through rest, energy is environmentally contingent on resource availability. Third, norm N7 (movement blocked when integrity is critical) is never activated in practice because the Ego anticipates the integrity threshold and rests before it is reached, demonstrating preventive norm compliance for the first time in the simulation series. Fourth, the viability threshold is gradual rather than sharp across tested wear rates, with delivery performance declining continuously. These findings establish that the multi-dimensional CC produces qualitatively richer dynamics than the scalar model and that CC dimensions exhibit fundamentally different controllability profiles requiring differentiated priority treatment in the Ego.

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Learning Without External Reward: Q-Learning in the ALI Ego Instance Evaluated Against the Causal Core Metric

Abstract: We replace the hardcoded BFS-based Ego of the ALI simulation with a Q-learning component evaluated against an internal reward signal derived exclusively from the causal core (CC). No external reward is provided. The agent learns to act solely on the basis of what preserves the system. Over 3000 training episodes, we document three distinct learning phases: an initial survival-only phase in which the agent stabilises self-preservation without task execution; a transition phase in which task execution emerges alongside stable survival; and a convergence phase in which deliveries increase while survival rate declines slightly. The central theoretical finding is that the CC metric as sole reward source is necessary but not sufficient to reproduce the explicit priority ordering of the hardcoded Ego. The learned Ego converges toward a slightly more aggressive task-execution strategy that sacrifices some self-preservation for higher delivery counts. This reveals that the architecture of the Ego contributes independently to the behavioral strategy: the explicit priority ordering (self-preservation before task) was not merely a convenience but a structural choice with behavioral consequences that Q-learning must approximate from reward signals alone. The results imply that learned Ego components in ALI deployments should be combined with explicit architectural constraints, and that the Super-Ego's veto power becomes correspondingly more important as a safety backstop when the Ego is a learning system.

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Two-Agent Dynamics in ALI: Emergent Behavior, Resource Competition, and Normative Resource Sharing

Abstract: We extend the Artificial Local Intelligence (ALI) simulation framework to a two-agent scenario. Two ALI agents with identical architecture operate in the same grid world without any communication protocol or shared representation. Each agent pursues local self-preservation through its causal core, executes a delivery task through its Ego instance, and is governed by a static Super-Ego. We introduce a fifth norm, N5, prohibiting agents from targeting a resource already claimed by the other agent when alternatives are available. Over 240 parameterised runs across four resource density levels and three respawn intervals, we document three emergent phenomena: implicit spatial segregation arising from positional asymmetry, structural resource exhaustion as a collective outcome of competing self-preservation drives, and a persistent positional advantage of the agent starting closer to the delivery station. The N5 comparison across 20 seeds reveals that normative resource sharing yields marginal or negative effects on total task performance when structural resource scarcity is the binding constraint. This finding establishes a general principle: normative architecture operates within, not above, environmental constraints. All observed collective phenomena emerge from purely local behavior without collective architecture, communication, or shared intentionality.

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Implementing the Causal Core: A Simulation of Artificial Local Intelligence

Abstract: This paper presents a Python simulation of an Artificial Local Intelligence (ALI) grounded in the theoretical framework of Stegemann (2025a). The simulation implements the causal core (CC) as an operative self-preservation principle rather than a data container, and distributes cognitive labor across three architecturally distinct instances: the CC as the operative self-preservation principle (Id), the Ego as the instance that solves the assigned task under the aspect of self-preservation, and the Super-Ego as the normative instance with veto power including the capacity for controlled self-shutdown. The paper documents the development from a scalar energy model (v1) to an architecturally corrected two-mode assimilation model (v2b), in which the carrying state is correctly assigned to the Ego rather than the CC, and task progress is treated as an external observation metric rather than an internal CC state. We analyze emergent behaviors observed during simulation runs: a norm-induced deadlock in v1 that illustrates a general property of static normative systems, a characteristic eat-deliver sequence in v2b that enacts the theoretical claim that the Ego solves tasks under the aspect of self-preservation, and idle phases during resource scarcity that show a locally bounded intelligence does not generate pseudo-tasks. The simulation operates without causal collapse and without qualia, demonstrating that self-preservation, task execution, and normative constraint are realizable in the complete absence of consciousness. We discuss the conditions under which this architecture could scale toward realistic ALI deployments and argue that the ALI is not a restricted version of AGI but a coherent counter-concept to it. The simulation code is available as open-source on GitHub.

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From the Myth of AGI to the Architecture of a Controllable ALI

Abstract: This discussion paper argues that the dominant concept of Artificial General Intelligence (AGI) suffers from two fundamental problems: a lack of conceptual clarity regarding purpose, and a structural impossibility of genuine intentionality without phenomenal consciousness. As an alternative, the paper develops the concept of an Artificial Local Intelligence (ALI): a locally bounded, purpose-specific agent that maintains itself in order to fulfill an assigned task, and remains controllable through built-in norms. The centrepiece of this architecture is the causal core (CC), a dynamic self-preservation principle derived from biology but detached from any organic instantiation. Drawing on Maturana and Varela's autopoiesis and contrasting the framework explicitly with Friston's Free Energy Principle, the paper proposes a three-instance architecture modeled loosely on Freud's structural model: the CC as operative self-preservation principle (Id), a situational decision-making instance that solves the task under the aspect of self-preservation (Ego), and a normative instance with veto power including the capacity for controlled self-shutdown (Super-Ego). The architecture is illustrated with a minimalist grid-world example. The paper argues that ALI is not a restricted version of AGI but a coherent counter-concept: a buildable, controllable, purpose-bound intelligence that operates without consciousness, intentionality, or causal collapse. A Python simulation implementing this framework is available on GitHub.

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DIMENSIONAL LOGIC: LLM EMPIRICS 2026

Abstract: Three leading Large Language Models spontaneously operationalize the 4-Dimension system of dimensional logic without any training: D1: Phenomenal (immediate perception) D2: Formal-systematic (predicate logic) D3: Reflexive-metacognitive (Theory of Mind) D4: Contextual-paradigmatic Result: 100% dimension understanding, perfect category error detection, correct transition operators.

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Adaptive Rationality through Dimensional Logic: Self-Adapting Operators in the Prisoner's Dilemma and in AI Systems

Abstract: This paper develops a novel framework of Dimensional Logic to extend the classical notion of rationality. Building on the metaphor of a “geometry of thought,” four cognitive dimensions (D1–D4) are formalized to show how rational decision-making evolves when reflexivity and contextuality are integrated. From this formalization emerge two operators: Δμ, representing the gains of reflexivity, and Δκ, capturing contextual coherence. Together, they expand the classical payoff function and explain why cooperation, rather than defection, becomes the rationally stable outcome. To demonstrate this, we present a Python-based simulation of the prisoner’s dilemma that includes adaptive operators. Results show that agents converge toward cooperative equilibria via self-adjustment mechanisms such as hill-climbing and self-play. Beyond game theory, the framework offers a generalizable model for adaptive rationality in artificial intelligence and multi-agent systems. It thereby bridges mathematical formalization, epistemic relativity, and practical applications in AI, suggesting a new path toward autonomous and context-sensitive decision architectures.

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