The concept of agency is of crucial importance in cognitive science and artificial intelligence, and it is often used as an intuitive and rather uncontroversial term, in contrast to more abstract and theoretically heavy-weighted terms like “intentionality”, “rationality” or “mind”. However, most of the available definitions of agency are either too loose or unspecific to allow for a progressive scientific program. They implicitly and unproblematically assume the features that characterize agents, thus obscuring the full potential and challenge of modeling agency. (...) We identify three conditions that a system must meet in order to be considered as a genuine agent: a) a system must define its own individuality, b) it must be the active source of activity in its environment (interactionalasymmetry) and c) it must regulate this activity in relation to certain norms (normativity). We find that even minimal forms of proto-celular systems can already provide a paradigmatic example of genuine agency. By abstracting away some specific details of minimal models of living agency we define the kind of organization that is capable to meet the required conditions for agency (which is not restricted to living organisms). On this basis, we define agency as an autonomous organization that adaptively regulates its coupling with its environment and contributes to sustaining itself as a consequence. We find that spatiality and temporality are the two fundamental domains in which agency spans at different scales. We conclude by giving an outlook to the road that lies ahead in the pursuit to understand, model and synthesis agents. (shrink)

The notion of information processing has dominated the study of the mind for over six decades. However, before the advent of cognitivism, one of the most prominent theoretical ideas was that of Habit. This is a concept with a rich and complex history, which is again starting to awaken interest, following recent embodied, enactive critiques of computationalist frameworks. We offer here a very brief history of the concept of habit in the form of a genealogical network-map. This serves to provide (...) an overview of the richness of this notion and as a guide for further re-appraisal. We identify 77 thinkers and their influences, and group them into seven schools of thought. Two major trends can be distinguished. One is the associationist trend, starting with the work of Locke and Hume, developed by Hartley, Bain, and Mill to be later absorbed into behaviorism through pioneering animal psychologists (Morgan and Thorndike). This tradition conceived of habits atomistically and as automatisms (a conception later debunked by cognitivism). Another historical trend we have called organicism inherits the legacy of Aristotle and develops along German idealism, French spiritualism, pragmatism, and phenomenology. It feeds into the work of continental psychologists in the early 20th century, influencing important figures such as Merleau-Ponty, Piaget, and Gibson. But it has not yet been taken up by mainstream cognitive neuroscience and psychology. Habits, in this tradition, are seen as ecological, self-organizing structures that relate to a web of predispositions and plastic dependencies both in the agent and in the environment. In addition, they are not conceptualized in opposition to rational, volitional processes, but as transversing a continuum from reflective to embodied intentionality. These are properties that make habit a particularly attractive idea for embodied, enactive perspectives, which can now re-evaluate it in light of dynamical systems theory and complexity research. (shrink)

In this article, we propose some fundamental requirements for the appearance of adaptivity. We argue that a basic metabolic organization, taken in its minimal sense, may provide the conceptual framework for naturalizing the origin of teleology and normative functionality as it appears in living systems. However, adaptivity also requires the emergence of a regulatory subsystem, which implies a certain form of dynamic decoupling within a globally integrated, autonomous system. Thus, we analyze several forms of minimal adaptivity, including the special case (...) of motility. We go on to explain how an open-ended complexity growth of motility-based adaptive agency, namely, behavior, requires the appearance of the nervous system. Finally, we discuss some implications of these ideas for embodied robotics. (shrink)

Living agency is subject to a normative dimension (good-bad, adaptive-maladaptive) that is absent from other types of interaction. We review current and historical attempts to naturalize normativity from an organism-centered perspective, identifying two central problems and their solution: (1) How to define the topology of the viability space so as to include a sense of gradation that permits reversible failure, and (2) how to relate both the processes that establish norms and those that result in norm-following behavior. We present a (...) minimal metabolic system that is coupled to a gradient-climbing chemotactic mechanism. Studying the relationship between metabolic dynamics and environmental resource conditions, we identify an emergent viable region and a precarious region where the system tends to die unless environmental conditions change. We introduce the concept of normative field as the change of environmental conditions required to bring the system back to its viable region. Norm-following, or normative action, is defined as the course of behavior whose effect is positively correlated with the normative field. We close with a discussion of the limitations and extensions of our model and some final reflections on the nature of norms and teleology in agency. (shrink)

Dynamicism has provided cognitive science with important tools to understand some aspects of “how cognitive agents work” but the issue of “what makes something cognitive” has not been sufficiently addressed yet, and, we argue, the former will never be complete without the later. Behavioristic characterizations of cognitive properties are criticized in favor of an organizational approach focused on the internal dynamic relationships that constitute cognitive systems. A definition of cognition as adaptive-autonomy in the embodied and situated neurodynamic domain is provided: (...) the compensatory regulation of a web of stability dependencies between sensorimotor structures, is created and preserved during a historical/developmental process. We highlight the functional role of emotional embodiment: internal bioregulatory processes coupled to the formation and adaptive regulation of neurodynamic autonomy. Finally, we discuss a “minimally cognitive behavior program” in evolutionary simulation modelling suggesting that much is to be learned from a complementary “minimally cognitive organization program”. (shrink)

The first form of the inside-outside dichotomy appears as a self-encapsulated system with an active border. These systems are based on two complementary but asymmetric processes: constructive and interactive. The former physically constitute the system as a recursive network of component production, defining an inside. The maintenance of the constructive processes implies that the internal organization also constrains certain flows of matter and energy across the border of the system, generating interactive processes. These interactive processes ensure the maintenance of the (...) constructive processes thus specifying a meaningful outside. Upon this basic form of identity formation, the evolutionary and historical domain is open for the emergence of a whole hierarchy and ecology of insides and outsides. These which mutually subsume and collaborate in the maintenance of the essential inside-outside dichotomy that defines the conditions of possibility of the subjects and the worlds they generate. (shrink)

There are many different kinds of model and scientists do all kind of things with them. This diversity of model type and model use is a good thing for science. Indeed, it is crucial especially for the biological and cognitive sciences, which have to solve many different problems at many different scales, ranging from the most concrete of the structural details of a DNA molecule to the most abstract and generic principles of self-organization in networks. Getting a grip (or more (...) likely many separate grips) on this range of topics calls for a teeming forest of techniques, including many different modeling techniques. Barbara Webb’s target article strikes us as a proposal for clear-cutting the forest. We think clear-cutting here would be as good for science as it is for non-metaphorical forests. Our argument for this is primarily a recitation of a few of the ways that diversity has been useful. Recently, looking at the actual practice of artificial life modelers, one of us distinguished four uses of simulation models classified in terms of the position the models take up between theory and data (see Figure 1). The classification is not exhaustive, and the barriers between kinds are not absolute. Rather, the purpose of the taxonomy is to open up the view for an epistemic ecology of modeling practices. First, and closest to the empirical domain, there are mechanistic models, in which there is an almost one-to-one correspondence between variables in the model and observables in the target system and its environment. Webb’s.. (shrink)

Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of theory (...) and experiment. ALife models become powerful epistemic artefacts allowing the simulation of emergent phenomena, the interaction between different levels of organization and the integration of different causal factors in the very same manipulable object. The use of computational models in ALife can be classified in four main categories depending on their position between theoretical and empirical practices: generic, conceptual, functional and mechanistic. For each of these categories we analyse their epistemic value and select paradigmatic examples that illustrate how ALife models can be fruitfully inserted in the study of life. (shrink)

This Open Access book explains the philosophy, design principles, and community organization of Decidim and provides essential insights into how the platform works. Decidim is the world leading digital infrastructure for participatory democracy, built entirely and collaboratively as free software, and used by more than 500 institutions with over three million users worldwide. -/- The platform allows any organization (government, association, university, NGO, neighbourhood, or cooperative) to support multitudinous processes of participatory democracy. In a context dominated by corporate-owned digital platforms, (...) in the era of increasing social structuring via Artificial Intelligence, Decidim stands as a public or community owned platform for collective human intelligence. Yet, the project is much more than its technological features. Decidim is in itself a crossroad of the various dimensions of the networked society, a detailed practical map of its complexities and conflicts. Theauthors distinguish three general dimensions of the project: (1) the political - shedding light on the democratic model that Decidim promotes and its impact on public policies and organizations, (2) the technopolitical - explaining how this technology is democratically designed and managed to produce and protect certain political effects, and (3) the technical - presenting the conditions of production, operation, and success of the project. This book systematically covers those three levels in an academically sound, technologically consistent, and politically innovative manner. Serving as a useful resource and handbook for the use of Decidim, it will not only appeal to students and scholars interested in participatory and digital democracy but also to professionals, policy-makers, and a wider audience interested in learning more about the Decidim platform. (shrink)