For millennia people have wondered what makes the living different from the non-living. Beginning in the mid-1980s, artificial life has studied living systems using a synthetic approach: build life in order to understand it better, be it by means of software, hardware, or wetware. This review provides a summary of the advances that led to the development of artificial life, its current research topics, and open problems and opportunities. We classify artificial life research into 14 themes: origins of life, autonomy, self-organization, adaptation (including evolution, development, and learning), ecology, artificial societies, behavior, computational biology, artificial chemistries, information, living technology, art, and philosophy. Being interdisciplinary, artificial life seems to be losing its boundaries and merging with other fields. Relevance: Artificial life has contributed to philosophy of biology and of cognitive science, thus making it an important field related to constructivism.

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.

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

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.

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

Living systems are characterized as self-generating and self-maintaining systems. This type of characterization allows integration of a wide variety of detailed knowledge in biology. The paper clarifies general notions such as processes, systems, and interactions. Basic properties of self-generating systems, i.e. systems which produce their own parts and hence themselves, are discussed and exemplified. This makes possible a clear distinction between living beings and ordinary machines. Stronger conditions are summarized under the concept of self-maintenance as an almost unique character of living systems. Finally, we discuss the far-reaching consequences that the principles of self-generation and self-maintenance have for the organization, structure, function, and evolution of singleand multi-cellular organisms.

This paper attempts to establish a systems-semiotic framework explaining creativity in the design process, where the design process is considered to have as its basis the cognitive process. The design process is considered as the interaction between two or more cognitive systems resulting in a purposeful and ongoing transformation of their already complex representational structures and the production of newer ones, in order to ful?ll an ill-defined goal. Creativity is considered as the result of an emergence of organizational complexity in each cognitive system participating in the design process, while it is trying to purposefully incorporate new constraints in its meaning structures. The meanings generated in each system are identi?ed as the contingent and anticipatory content of its representations, and where self-organization is the dominant process in which they are continuously involved. Furthermore, Peircean semiotic processes appear to provide the functionality needed by the emergent representational structures in order to complete the cycle of a creative design process. Creativity originates in the abductive stage of the semiotic process, the fallible nature of which is maintained in the proposed framework by the fact that the respective emergent representations can be mis?ts. The nodal points of the framework are identified and analyzed showing that a cognitive system needs the whole interactive anticipatory cycle in order to engage in a creative design process.

Key words: Anticipations, Creativity, Emergent Representations, Peircean Semiotic Processes, Self-organization

Contemporary research in artificial environments has marked the need for autonomy in artificial agents. Autonomy has many interpretations in terms of the field within which it is being used and analyzed, but the majority of the researchers in artificial environments are arguing in favor of a strong and life-like notion of autonomy. Departing from this point the main aim of this paper is to examine the possibility of the emergence of autonomy in contemporary artificial agents. The theoretical findings of research in the areas of living and cognitive systems, suggests that the study of autonomous agents should adopt a systemic and emergent perspective for the analysis of the evolutionary development of the notions/properties of autonomy, functionality, intentionality and meaning, as the fundamental and characteristic properties of a natural agent. An analytic indication of the functional emergence of these concepts and properties is provided, based on the characteristics of the more general systemic framework of second-order cybernetic and of the interactivist framework. The notion of emergence is a key concept in such an analysis which in turn provides the ground for the theoretical evaluation of the autonomy of contemporary artificial agents with respect to the functional emergence of their capacities. The fundamental problems for the emergence of genuine autonomy in artificial agents are critically discussed and some design guidelines are provided.

Key words: Agency, Autonomy, Downward Causation, Functionality, Intentionality, Meaning, Normativity, Self-organization, emergence

The so-called rigor–relevance gap appears unbridgeable in the classical view of organization science, which is based on the physical sciences’ model. Constructivist scholars have also pointed out a certain inadequacy of this model of science for organization research, but they have not offered an explicit, alternative model of science. Responding to this lack, this paper brings together the two separate paradigmatic perspectives of constructivist epistemologies and of organizational design science, and shows how they could jointly constitute the ingredients of a constructivism-founded scientific paradigm for organization research. Further, the paper highlights that, in this constructivist view of organizational design science, knowledge can be generated and used in ways that are mutually enriching for academia and practice

In this paper we argue for the possibilities of applying the concept of autopoiesis to the information systems of modern organizations. Modern organizations in today’s rapidly changing, turbulent and complex environment are virtual, open, heterarchic and autopoietic. The main question we try to address in this paper is how to support these organizations with an adequate information system. We show that it is possible to develop autopoietic information systems that should be able to respond to the challenges of modern organizations.

Key words: autopoiesis, information system, organization