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

Predictive processing (PP) approaches to the mind are increasingly popular in the cognitive sciences. This surge of interest is accompanied by a proliferation of philosophical arguments, which seek to either extend or oppose various aspects of the emerging framework. In particular, the question of how to position predictive processing with respect to enactive and embodied cognition has become a topic of intense debate. While these arguments are certainly of valuable scientific and philosophical merit, they risk underestimating the variety of approaches gathered under the predictive label. Here, we first present a basic review of neuroscientific, cognitive, and philosophical approaches to PP, to illustrate how these range from solidly cognitivist applications – with a firm commitment to modular, internalistic mental representation – to more moderate views emphasizing the importance of ‘body-representations’, and finally to those which fit comfortably with radically enactive, embodied, and dynamic theories of mind. Any nascent predictive processing theory (e.g., of attention or consciousness) must take into account this continuum of views, and associated theoretical commitments. As a final point, we illustrate how the Free Energy Principle (FEP) attempts to dissolve tension between internalist and externalist accounts of cognition, by providing a formal synthetic account of how internal ‘representations’ arise from autopoietic self-organization. The FEP thus furnishes empirically productive process theories (e.g., predictive processing) by which to guide discovery through the formal modelling of the embodied mind.

Key words: Predictive processing, embodied cognition, interoception, active inference, connectionism, computationalism, enactivism.

Context: The enactivist tradition, out of which neurophenomenology arose, rejects various internalisms – including the representationalist and information-processing metaphors – but remains wedded to one further internalism: the claim that the structure of perceptual experience is directly, constitutively linked only to internal, brain-based dynamics. Problem: I aim to reject this internalism and defend an alternative analysis. Method: The paper presents a direct-realist, externalist, sensorimotor account of perceptual experience. It uses the concept of counterfactual meaningful action to defend this view against various objections. Results: This account of experience matches certain first-person features of experience better than an internalist account could. It is fully tractable as “normal science.” Implications: The neuroscientific conception of brain function should change from that of internal representation or modelling to that of enabling meaningful, embodied action in ways that constitutively involve the world. Neurophenomenology should aim to match the structure of first-person experience with the structure of meaningful agent-world interactions, not with that of brain dynamics. Constructivist content: The sensorimotor approach shows us what external objects are, such that we may enact them, and what experience is, such that it may present us with those enacted objects.

Key words: Neurophenomenology, perception, experience, sensorimotor contingency theory, direct realism, externalism, qualia, counterfactuals

Context: The discipline of knowledge management (KM) begins to understand a) that it should move towards a user-centred, socialized KM and b) which business objectives provide motivation to do so. However, it lacks ideas on how to reach the objective that it suggests and justifies. We contend in this paper that this change requires a more viable understanding of knowledge combined with a suitable model of social interaction, otherwise it will fail. Problem: The problem to be solved is to find a way to blend a model of social interaction and a suitable understanding of knowledge so that together they can contribute to the objective of implementing a “user-centred KM.” In this paper we show a solution articulated in several conceptual and experimental components and phases. Method: We use a systemic and cybernetic approach: systemic analysis of the problem, conception of a cybernetic approach, design of a systemic solution, and its evaluation in an experiment. The main methods used are systems engineering, cybernetic modelling, and knowledge engineering. Results: We propose seven interrelated results: 1. A defect analysis of KM; 2. The concept of knowledge as the “Logic of Experience”; 3. A set of five KM design principles; 4. The principle of “Knowledge Identity”; 5. The model of “Knowledge Cooperation”; 6. The architecture of a user-centred KM system; and 7. Insights from a KM experiment. Implications: Our results are useful for any stakeholder in today’s knowledge economy when they need to understand, design, build, nurture and support an organization’s capacity to learn and innovate for the benefit not only of the company’s financial owners but also of the individuals who work in it. Future research should urgently address the issues of “knowledge identity” and the “knowledge contract” and KM practice should design its next steps for moving towards a user-centred KM in conformity with the principle of “knowledge identity.” The paper links explicitly to radical constructivism and argues in favour of a radical constructivist foundation for KM in which knowledge is seen as the “Logic of Experience.” It also shows how this KM foundation can be extended with a social perspective and by that allow the individual and the social to be conceived of as complementary elements in one single KM system.

Key words: logic of experience, knowledge identity, knowledge cooperation, design for meaning, community of research, user-centred knowledge management

The merits of Empirical Modelling (EM) principles and tools as a constructivist approach to computer science education are illustrated with reference to ways in which they have been used in teaching topics related to the standard computer science curriculum. The products of EM are interactive models – construals – that serve a sense-making role. Model-building proceeds in an incremental fashion through the construction of networks of definitions that reflect the observables, dependencies and agents associated with a current situation. The three principal case studies discussed (teaching bubblesort, solving Sudoku puzzles, and recognising groups from their abstract multiplication tables) highlight respects in which EM accounts for aspects of computing that cannot be effectively addressed by thinking primarily in terms of abstractions, procedures and mechanisms. The discussion of EM as a constructivist approach to computer science education is set in the context of an analysis of constructivism in computer science published by Ben-Ari in 2001. Reconciling EM’s constructivist epistemology with this analysis involves recognising its pretensions to a broader view of computer science.

Educational technology is seen as key for lifelong learning, but it has yet to live up to expectation. We argue that current learning environments are typically oriented too much towards structured learning to meet the needs of the lifelong learner. Environments for lifelong learning demand a higher degree of autonomy for the learner, must be open to eclectic sources, support soft informal learning activity, and accommodate evolution both in the experience of the learner and in the context in which this occurs. We propose sense-making through the construction of suitable interactive artefacts as a core activity for lifelong learning, and discuss and illustrate how this can be supported using Empirical Modelling. The merits of Empirical Modelling as a constructivist approach are assessed with reference to a criterion recently proposed by Bruno Latour, namely, the extent to which it strengthens five guarantees, taken together.

This Introduction is our attempt to clarify further the cluster of key notions: autonomy, viability, abduction and adaptation. These notions form the conceptual scaffolding within which the individual contribution contained in this volume can be placed. Hopefully, these global concepts represent fundamental signposts for future research that can spare us a mere flurry of modelling and simulations into which this new field could fall.

Key words: cognitivism, connectionism, enaction, autonomy, viability, abduction, adaptation

This paper discusses various suggestions for a philosophical framework for a trans-disciplinary information science or a semiotic doctrine. These are: the mechanical materialistic, the pan-informational, the Luhmanian second order cybernetic approach, Peircian biosemiotics and finally the pan-semiotic approach. The limitations of each are analysed. The conclusion is that we will not have to choose between either a cybernetic-informational or a semiotic approach. A combination of a Peircian-based biosemiotics with autopoiesis theory, second order cybernetics and information science is suggested in a five-levelled cybersemiotic framework. The five levels are 1) a level of Firstness, 2) a level of mechanical matter, energy and force as Secondness, 3) a cybernetic and thermodynamic level of information, 4) a level of sign games and 5) a level of conscious language games. These levels are then used to differentiate levels of information systems, sign and language games in human communication. In our model Maturana and Varela’s description of the logic of the living as autopoietic is accepted and expanded with Luhmann’s generalization of the concept of autopoiesis, to cover also to psychological and socio-communicative systems. Adding a Peircian concept of semiosis to Luhmann’s theory in the framework of biosemiotics enables us to view the interplay of mind and body as a sign play. I have in a previous publication (see list of references) suggested the term “sign play” pertaining to exosemiotics processes between animals in the same species by stretching Wittgenstein’s language concept into the animal world of signs. The new concept of intrasemiotics designates the semiosis of the interpenetration between biological and psychological autopoietic systems as Luhmann defines them in his theory. One could therefore view intrasemiotics as the interplay between Lorenz’ biological defined motivations and Freud’s Id, understood as the psychological aspect of many of the natural drives. In the last years of the development of his theory, Lorenz worked with the idea of how emotional feedback introduced just a little learning through pleasurable feelings into instinctive systems because, as he reasoned, there must be some kind of reward of going through instinctive movements, thus making possible the appetitive searching behaviour for sign stimuli. But he never found an acceptable way of modelling motivation in biological science. I am suggesting a cybersemiotic model to combine these approaches, defining various concepts like thought-semiotics, phenosemiotic and intrasemiotics, combining them with the already known concepts of exosemiotics, ecosemiotics, and endosemiotics into a new view of self-organizing semiotic processes in living systems. Thus a new semiotic level of description is generated, where mind-body interactions can be understood on the same description level.

Key words: Cybersemiotics, cybernetics, semiotics, information, self-organisation

A common assumption in teaching mathematical modelling and applications is that mind and world are ontologically distinct. This dualist view give rise to an explanatory gap as to how these two realms connect. An alternate view where mind and world are ontologically identical is explored here. This alternate view, grounded in a monist ontology of embodied cognition, undermines and attempts to fill this explanatory gap. Embodied cognition presents challenges of its own, but it also presents new pedagogical opportunities.

This paper outlines an original interactivist–constructivist (I-C) approach to modelling intelligence and learning as a dynamical embodied form of adaptiveness and explores some applications of I-C to understanding the way cognitive learning is realized in the brain. Two key ideas for conceptualizing intelligence within this framework are developed. These are: (1) intelligence is centrally concerned with the capacity for coherent, context-sensitive, self-directed management of interaction; and (2) the primary model for cognitive learning is anticipative skill construction. Self-directedness is a capacity for integrative process modulation which allows a system to “steer” itself through its world by anticipatively matching its own viability requirements to interaction with its environment. Because the adaptive interaction processes required of intelligent systems are too complex for effective action to be prespecified (e.g. genetically) learning is an important component of intelligence. A model of self-directed anticipative learning (SDAL) is formulated based on interactive skill construction, and argued to constitute a central constructivist process involved in cognitive development. SDAL illuminates the capacity of intelligent learners to start with the vague, poorly defined problems typically posed in realistic learning situations and progressively refine them, transforming them into problems with sufficient structure to guide the construction of a solution. Finally, some of the implications of I-C for modelling of the neuronal basis of intelligence and learning are explored; in particular, Quartz and Sejnowski’s recent neural constructivism paradigm, enriched by Montague and Sejnowski’s dopaminergic model of anticipative–predictive neural learning, is assessed as a promising, but incomplete, contribution to this approach. The paper concludes with a fourfold reflection on the divergence in cognitive modelling philosophy between the I-C and the traditional computational information processing approaches.