This article examines the intellectual and institutional factors that contributed to the col- laboration of neuropsychiatrist Warren McCulloch and mathematician Walter Pitts on the logic of neural networks, which culminated in their 1943 publication, “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Historians and scientists alike often refer to the McCulloch–Pitts paper as a landmark event in the history of cybernetics, and fundamental to the development of cognitive science and artificial intelligence. This article seeks to bring some historical context to the McCulloch–Pitts collaboration itself, namely, their intellectual and scientific orientations and backgrounds, the key concepts that contributed to their paper, and the institutional context in which their collaboration was made. Al- though they were almost a generation apart and had dissimilar scientific backgrounds, McCulloch and Pitts had similar intellectual concerns, simultaneously motivated by issues in philosophy, neurology, and mathematics. This article demonstrates how these issues converged and found resonance in their model of neural networks. By examining the intellectual backgrounds of McCulloch and Pitts as individuals, it will be shown that besides being an important event in the history of cybernetics proper, the McCulloch– Pitts collaboration was an important result of early twentieth-century efforts to apply mathematics to neurological phenomena.

Recently, historians have focused on Warren S. McCul¬loch’s role in the cybernetics movement during the 1940s and 1950s, and his contributions to the develop¬ment of computer science and communication theory. What has received less attention is McCulloch’s early work in neurophysiology, and its relationship to his philosophical quest for an ‘experimental epistemology’ – a physiological theory of knowledge. McCulloch’s early laboratory work during the 1930s addressed the problem of cerebral localization: localizing aspects of behaviour in the cerebral cortex of the brain. Most of this research was done with the Dutch neurophysiolo¬gist J. G. Dusser de Barenne at Yale University. The con¬nection between McCulloch’s philosophical interests and his experimental work can be expressed as a search for a physiological a priori, an integrated mechanism of sensation.

In this article we analyze the methodological commitments of a radical embodied cognition (REC) approach to social interaction and social cognition, specifically with respect to the explanatory framework it adopts. According to many representatives of REC, such as enactivists and the proponents of dynamical and ecological psychology, sociality is to be explained by (1) focusing on the social unit rather than the individuals that comprise it and (2) establishing the regularities that hold on this level rather than modeling the sub-personal mechanisms that could be said to underlie social phenomena. We point out that, despite explicit commitment, such a view implies an implicit rejection of the mechanistic explanation framework widely adopted in traditional cognitive science (TCS), which, in our view, hinders comparability between REC and these approaches. We further argue that such a position is unnecessary and that enactive mechanistic explanation of sociality is both possible and desirable. We examine three distinct objections from REC against mechanistic explanation, which we dub the decomposability, causality and extended cognition worries. In each case we show that these complaints can be alleviated by either appreciation of the full scope of the mechanistic account or adjustments on both mechanistic and REC sides of the debate.

Key words: enactivism, mechanistic explanation, social cognition

In this paper we examine an enactive approach to social cog- nition, a species of radical embodied cognition typically pro- posed as an alternative to traditional cognitive science. Ac- cording to enactivists, social cognition is best explained by reference to the social unit rather than the individuals that par- ticipate in it. We identify a methodological problem in this approach, namely a lack of clarity with respect to the model of explanation it adopts. We review two complaints about a mechanistic explanatory framework, popular in traditional cognitive science, that prevent enactivists from embracing it. We argue that these complaints are unfounded and propose a conceptual model of enactive mechanistic explanation of so- cial cognition.

Key words: enactivism, social cognition, mechanistic expla- nation

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.

Open peer commentary on the article “Missing Colors: The Enactivist Approach to Perception” by Adrián G. Palacios, María-José Escobar & Esteban Céspedes. Upshot: The target article discusses the influence of the enactivist account of perception in computer science, beyond subjectivism and objectivism. I suggest going one step further and introduce our VirtualEnaction platform, proposing a federative systemic view for brain-body-environment interaction for this analysis.

The aim of this paper is to reconsider some of the stakes involved in the dialogue between sciences and between scientists, considering it as a complex and critical learning process. Dialogue – as conversation, expression, performance and negotiation – can be conceived in several ways. It carries both an epistemic and an experiential side. It involves simultaneously heterogeneous theories and identities. Because it involves fragmented scientific languages, it also requires a shared vision. But above all, what seems critical to acknowledge is that dialogue is a matter of transformation. And because transformation is also a matter of learning, the promotion of dialogue between sciences should be perceived as a virtuous spiral involving: instrumental learning (to dialogue), communicational learning (what we mean by dialoguing) and emancipatory learning (to challenge our core assumptions about dialogue and sciences). Considering the evolution of sciences as a double process embedded in the production of knowledge and the self-development of researchers raises the question of how to conceive simultaneously the relationships between these two major stakes. From a practical point of view, considering scientific dialogue as a lifelong learning process would finally suggest the management of forums like the World Knowledge Dialogue (WKD) as a privileged educational opportunity to be designed following what is known about science as a social practice and about researchers as adult learners. Based on the first edition of this forum, four suggestions are finally considered: favoring heterogeneity; valorizing formal knowledge as well as lived experience; acknowledging the learning dimension involved in the process of sharing; and confronting professional experience with knowledge produced about sciences. Inspired by Edgar Morin’s constructivist and non-dualistic position, this paper explores its practical stakes by revisiting the practice of transdisciplinary research and by considering the relationships between the process of knowledge construction and researchers’ self-development as a lifelong learning process.

This paper undertakes a theoretical investigation of the “learning” aspect of science as opposed to the “knowledge” aspect. The practical background of the paper is in agricultural systems research – an area of science that can be characterised as “systemic” because it is involved in the development of its own subject area, agriculture. And the practical purpose of the theoretical investigation is to contribute to a more adequate understanding of science in such areas, which can form a basis for developing and evaluating systemic research methods, and for determining appropriate criteria of scientific quality. Two main perspectives on science as a learning process are explored: research as the learning process of a cognitive system, and science as a social, communicational system. A simple model of a cognitive system is suggested, which integrates both semiotic and cybernetic aspects, as well as a model of self-reflective learning in research, which entails moving from an inside “actor” stance to an outside “observer” stance, and back. This leads to a view of scientific knowledge as inherently contextual and to the suggestion of reflexive objectivity and relevance as two related key criteria of good science.

Key words: Agriculture, cognition, communication, experiential, learning, research, science, self-reflective, systemic

The paradox of scientific expertise is that the growth of science leads to a fragmentation of scientific expertise. To resolve this paradox, this paper probes three hypotheses: 1) All scientific knowledge is perspectival. 2) The perspectival structure of science leads to specific forms of knowledge asymmetries. 3) Such perspectival knowledge asymmetries must be handled through second order perspectives. We substantiate these hypotheses on the basis of a perspectivist philosophy of science grounded in Peircean semiotics and autopoietic systems theory. Perspectivism is an important elaboration of constructivist approaches to help overcome problems in cross-disciplinary collaboration and use of science, and thereby make society better able to solve complex, real-world problems.

Context: The problems that are most in need of interdisciplinary collaboration are “wicked problems,” such as food crises, climate change mitigation, and sustainable development, with many relevant aspects, disagreement on what the problem is, and contradicting solutions. Such complex problems both require and challenge interdisciplinarity. Problem: The conventional methods of interdisciplinary research fall short in the case of wicked problems because they remain first-order science. Our aim is to present workable methods and research designs for doing second-order science in domains where there are many different scientific knowledges on any complex problem. Method: We synthesize and elaborate a framework for second-order science in interdisciplinary research based on a number of earlier publications, experiences from large interdisciplinary research projects, and a perspectivist theory of science. Results: The second-order polyocular framework for interdisciplinary research is characterized by five principles. Second-order science of interdisciplinary research must: 1. draw on the observations of first-order perspectives, 2. address a shared dynamical object, 3. establish a shared problem, 4. rely on first-order perspectives to see themselves as perspectives, and 5. be based on other rules than first-order research. Implications: The perspectivist insights of second-order science provide a new way of understanding interdisciplinary research that leads to new polyocular methods and research designs. It also points to more reflexive ways of dealing with scientific expertise in democratic processes. The main challenge is that this is a paradigmatic shift, which demands that the involved disciplines, at least to some degree, subscribe to a perspectivist view. Constructivist content: Our perspectivist approach to science is based on the second-order cybernetics and systems theories of von Foerster, Maruyama, Maturana & Varela, and Luhmann, coupled with embodied theories of cognition and semiotics as a general theory of meaning from von Uexküll and Peirce.

Key words: Perspectivism, semiotics, complex phenomena, social systems theory, differentiation of science, perspectival knowledge asymmetries.