In the present essay we attempt to reconstruct Newtonian mechanics under the guidance of logical principles and of a constructive approach related to the genetic epistemology of Piaget and García (Psychogenesis and the history of science, Columbia University Press, New York, 1989). Instead of addressing Newton’s equations as a set of axioms, ultimately given by the revelation of a prodigious mind, we search for the fundamental knowledge, beliefs and provisional assumptions that can produce classical mechanics. We start by developing our main tool: the no arbitrariness principle, that we present in a form that is apt for a mathematical theory as classical mechanics. Subsequently, we introduce the presence of the observer, analysing then the relation objective–subjective and seeking objectivity going across subjectivity. We take special care of establishing the precedence among all contributions to mechanics, something that can be better appreciated by considering the consequences of removing them: (a) the consequence of renouncing logic and the laws of understanding is not being able to understand the world, (b) renouncing the early elaborations of primary concepts such as time and space leads to a dissociation between everyday life and physics, the latter becoming entirely pragmatic and justifed a-posteriori (because it is convenient), (c) changing our temporary beliefs has no real cost other than efort. Finally, we exemplify the present approach by reconsidering the constancy of the velocity of light. It is shown that it is a result of Newtonian mechanics, rather than being in contradiction with it. We also indicate the hidden assumption that leads to the (apparent) contradiction.

Key words: newtonian mechanics, no arbitrariness principle, objective versus subjective description, law of inertia, central forces, energy conservation, laws of nature, genetic epistemology.

According to the free energy principle all living systems aim to minimise free energy in their sensory exchanges with the environment. Processes of free energy minimisation are thus ubiquitous in the biological world. Indeed it has been argued that even plants engage in free energy minimisation. Not all living things however feel alive. How then did the feeling of being alive get started? In line with the arguments of the phenomenologists, I will claim that every feeling must be felt by someone. It must have mineness built into it if it is to feel a particular way. The question I take up in this paper asks how mineness might have arisen out of processes of free energy minimisation, given that many systems that keep themselves alive lack mineness. The hypothesis I develop in this paper is that the life of an organism can be seen as an inferential process. Every living system embodies a probability distribution conditioned on a model of the sensory, physiological, and morphological states that are highly probably given the life it leads and the niche it inhabits. I argue for an ecological and enactive interpretation of free energy. I show how once the life of an organism reaches a certain level of complexity mineness emerges as an intrinsic part of the process of life itself.

Key words: free energy principle, mineness, minimal self, ecological enactive, active inference, relational self, multisensory integration, bayesian brain.

Predictive processing (PP) has been repeatedly presented as a unificatory account of perception, action, and cognition. In this paper, we argue that this is premature: As a unifying theory, PP fails to deliver general, simple, homogeneous, and systematic explanations. By examining its current trajectory of development, we conclude that PP remains only loosely connected both to its computational framework and to its hypothetical biological underpinnings, which makes its fundamentals unclear. Instead of offering explanations that refer to the same set of principles, we observe systematic equivocations in PP-based models, or outright contradictions with its avowed principles. To make matters worse, PP-based models are seldom empirically validated, and they are frequently offered as mere just-so stories. The large number of PP-based models is thus not evidence of theoretical progress in unifying perception, action, and cognition. On the contrary, we maintain that the gap between theory and its biological and computational bases contributes to the arrested development of PP as a unificatory theory. Thus, we urge the defenders of PP to focus on its critical problems instead of offering mere re-descriptions of known phenomena, and to validate their models against possible alternative explanations that stem from different theoretical assumptions. Otherwise, PP will ultimately fail as a unified theory of cognition.

Events and event prediction are pivotal concepts across much of cognitive science, as demonstrated by the papers in this special issue. We first discuss how the study of events and the predictive processing framework may fruitfully inform each other. We then briefly point to some links to broader philosophical questions about events.

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.

The emergence of mind is a central issue in cognitive philosophy. The main working assumption of the present paper is that several important insights in answering this question might be provided by the nature of life itself. It is in this line of thinking that this paper compares two major philosophical conceptualizations of the living in the history of theoretical biology, namely those of Maturana and Aristotle. The present paper shows how both thinkers describe the most fundamental properties of the living as autonomous sustenance. The paper also shows how these theoretical insights might have a consequence upon our understanding of a specific constructiveness of human cognition, here referred to as enarrativity, if this can be considered in a structural as well as evolutionary connection with the structure of life as such. The paper finally suggests that the structural connection made here can be traced from the fundamental organization of self-preservation to survival behaviors to constructive orientation and action.

Key words: autopoiesis, soul, system theory, organism, cognitive philosophy, enarrativity, theoretical biology.

In a recent paper, Jakob Hohwy argues that the emerging predictive processing (PP) perspective on cognition requires us to explain cognitive functioning in purely internalistic and neurocentric terms. The purpose of the present paper is to challenge the view that PP entails a wholesale rejection of positions that are interested in the embodied, embedded, extended, or enactive dimensions of cognitive processes. I will argue that Hohwy’s argument from analogy, which forces an evidentiary boundary into the picture, lacks the argumentative resources to make a convincing case for the conceptual necessity to interpret PP in solely internalistic terms. For this reason, I will reconsider the postulation and explanatory role of the evidentiary boundary. I will arrive at an account of prediction error minimization and its foundation on the free energy principle that is fully consistent with approaches to cognition that emphasize the embodied and interactive properties of cognitive processes. This gives rise to the suggestion that explanatory pluralism about the application of PP is to be preferred over Hohwy’s explanatory monism that follows from his internalistic and neurocentric view of predictive cognitive systems.

Key words: dynamical systems theory, embodied cognition, explanatory pluralism, free energy principle, prediction error minimization.

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.

While the phenomena of reaching a goal is generally represented in the framework of optimization, the phenomena of becoming of a goal is more similar to a “self-organization and emergent” rather than an “optimization and preexisting” process. In this article we provide a modeling framework for the former alternative by representing goals as emergent autopoietic structures. In order to conceptually situate our approach, we first review some of the most remarkable attempts to formally define emergence, and identify that in most cases such definitions rely on a preexisting system to be observed prior and post emergence, being thus inadequate for a formalization of emergent goals corresponding to the becoming of a systems as such (e.g. emergence of life). Next, we review how an implementation of the reaction networks framework, known as Chemical Organization Theory (COT), can be applied to formalize autopoietic structures, providing a basis to operationalize goals as an emergent process. We next revisit the definitions of emergence under the light of our approach, and demonstrate that recent taxonomies developed to classify different forms of emergence can be naturally deduced from recent work aimed to explain the kinds of changes of the organizational structure of a reaction network.

Key words: chemical organization theory, emergence, goals, autopoiesis, process modelling.

This article presents a history of ‘Project Cybersyn’, an early computer network developed in Chile during the socialist presidency of Salvador Allende (1970–1973) to regulate the growing social property area and manage the transition of Chile’s economy from capitalism to socialism. Under the guidance of British cybernetician Stafford Beer, often lauded as the ‘father of management cybernetics’, an interdisciplinary Chilean team designed cybernetic models of factories within the nationalised sector and created a network for the rapid transmission of economic data between the government and the factory floor. The article describes the construction of this unorthodox system, examines how its structure reflected the socialist ideology of the Allende government, and documents the contributions of this technology to the Allende administration.