In this paper we present a new model for the mechanism underlying what is traditionally known in immunology as the “selfnonself” distinction. It turns out that in operational terms, the distinction effected by this model of the immune system is between a sufficiently numerous set of antigens present from the start of the ontogeny of the system on the one hand, and isolated antigens first introduced after the system has reached maturity on the other. The coincidence between this “founder versus late” distinction and the traditional “somatic self-foreign pathogen” one is essentially contingent, an example of the purely opportunistic tinkering characteristic of biological organization in general. We conclude that the so-called “self-nonself” distinction in immunology is a misleading misnomer. This raises the question as to what would genuinely count as a “self-nonself” distinction, a fundamental question for biology in general and Artificial Life in particular.

In what ways can artificial life contribute to the scientific exploration of cognitive, affective and social processes? In what sense can synthetic models be relevant for the advancement of behavioral and cognitive sciences? This article addresses these questions by way of a case study – an interdisciplinary cooperation between developmental robotics and developmental psychology in the exploration of attachment bonds. Its main aim is to show how the synthetic study of cognition, as well as the synthetic study of life, can find in autopoietic cognitive biology more than a theory useful to inspire the synthetic modelling of the processes under inquiry. We argue that autopoiesis offers, not only to artificial life, but also to the behavioural and social sciences, an epistemological framework able to generate general criteria of relevance for synthetic models of living and cognitive processes. By “criteria of relevance” we mean criteria (a) valuable for the three main branches of artificial life (soft, hard, and wet) and (b) useful for determining the significance of the models each branch produces for the scientific exploration of life and cognition. On the basis of these criteria and their application to the case study presented, this article defines a range of different ways that synthetic, and particularly autopoiesis-based models, can be relevant to the inquiries of biological, behavioural and cognitive sciences.

In the field of artificial life there is no agreement on what defines ‘autonomy’. This makes it difficult to measure progress made towards understanding as well as engineering autonomous systems. Here, we review the diversity of approaches and categorize them by introducing a conceptual distinction between behavioral and constitutive autonomy. Differences in the autonomy of artificial and biological agents tend to be marginalized for the former and treated as absolute for the latter. We argue that with this distinction the apparent opposition can be resolved.

Abstract. Biology is, better than anything else, about existence in time. Hence biological reality cannot be defined without reference to a temporally situated observer. The coupled or detached character of this observer (with respect to the own time variable of the system) provides a link between the observer and the observed. This connections delimits the kinds of scientific descriptions that can be given at all by an observer. In particular, two fundamentally different forms of description, corresponding to different epistemological attitudes and different philosophies of science, called endo- and exo-physics, can be distinguished. Two old puzzles, the Omniscience Problem (illustrated here on the example of Internal Chemistry) and the Chameleon Problem (originally an argument against philosophical functionalism) are reconsidered in the light of these distinctions. As application, the question, in what sense computer models of life can be suitable for studying life, is examined.

This paper aims at understanding modular organization in multivariate dynamical data. In contrast to information-theoretic approaches, the authors start from the complementary point of view of statistical modeling and prediction of dynamical systems. They arrive at the conclusion that modularity is not necessarily an objective property of a system’s organization but rather is inferred by cognitive systems as it can simplify learning and lead to gains in predictive power. This conclusion may prove useful for constructivist approaches as the paper establishes in formal ways that learning agents may perceive modularity and correlations among variables in their environments, even when such variables are actually dependent on others.

Since the concept of autopoiesis was proposed as a model of minimal living systems by Maturana and Varela, there has been still few mathematically strict models to represent the characteristics of it because of its difficulty for interpretation. This paper proposes a formal description of autopoiesis based on the theory of category and Rosen’s perspective of “closure under efficient cause.”

Some research works have mentioned the similarity of autopoiesis with (M, R) systems proposed by Rosen, from the perspective of closedness of the systems. However, there are some difference between the aspects of closedness required for autopoiesis and (M, R) systems. This paper aims at clarifying these differences to investigate the possibility of algebraic description of living systems, based on category theoretic frameworks.

A framework for understanding and exploiting embodiment is presented which is not dependent on any specific ontological context. This framework is founded on a new definition of embodiment, based on the relational dynamics that exist between biological organisms and their environments, and inspired by the structural dynamics of the bacterium Escherichia coli. Full recognition is given to the role played by physically instantiated bodies, but in such a way that this can be meaningfully abstracted within the constraints implied by the term ‘embodiment’, and applied in a variety of operational contexts. This is illustrated by ongoing experimental work in which the relational dynamics that exist between E. coli and its environment are applied in a variety of software environments, using Cellular Automata (CA) with artificial’ sensory’ and’ effector’ surfaces, producing qualitatively similar’ chemotactic’ behaviours in a variety of operational domains.

One major criticism of direct or active perception (and other forms of embodied action) from the perspective of cognitive psycology is that, according to common sense, there are some actions that require strictly symbolic information – for example, to stop a car in response to a red traffic light – which fall outside the realm of a perception-action cycle. Although such cognitive responses are not necessarily a goal of artificial life, they must necessarily be included within the embodied paradigm if it is to encompass the cognisant individual, the self-aware individual, or, potentially, the conscious individual. This paper will address the question, ‘can an animat appreciate art?’ Although this may seem very different to the example of a prosaic response to a traffic light, it will be argued that a common framework for establishing the meaning of an object is needed. It will also be argued that clarification to previous philosophical models of artistic engagement is required: in particular that the process of understanding is not a dialogue between an autopoietic artwork and animat, but that there is either a unity of object (artworkanimat) which becomes self-maintaining, or a more classical Gibsonian interpretation as a fixed set of affordances offered by an object to the subject, both of which lead to the conclusion that the process of understanding becomes a resonance in the unity or animat.

Key words: Autopoiesis, hermeneutics, embodiment, phenomenology, direct perception, natural vision

The lack within AL of an agreed-upon notion of life and of a set of criteria for identifying life is considered. I propound a reflection upon the codified nature of the organization of living beings. The necessity of a guiding notion based on the coding is defended. After sketching some properties of the genetic code I proceed to consider the issue of functionalism as strategy for AL. Several distinctions ranging from plain multiple realizability to total implementation independence are made, arguing that the different claims should not be confused. The consideration of the semantic and intrinsically meaningful nature of the code leads to discuss the “symbol grounding” in AL. I suggest the principle of Semantic Closure as a candidate for confronting both problems inasmuch as it can be considered an accurate guiding notion to semantically ground Artificial Life.