Purpose: To point out the relevance of Heinz von Foerster’s work to modern embodied cognitive science and artificial intelligence research. Approach: The paper discusses (a) von Foerster’s contributions to understanding the limitations of the computer metaphor which has long dominated cognitive science, and (b) his theories concerning how reality is constructed in organizationally closed organisms, and what the underlying neural mechanisms are. The latter is exemplified with a simple neuro-robotic model that illustrates the constructive and anticipatory nature of memory. Findings: von Foerster’s work on the integration of a radical constructivist philosophy of knowledge construction with models of the underlying neurophysiological and sensorimotor mechanisms is still highly relevant to the understanding of embodied cognition and robotic models thereof. Value: This paper identifies conceptual contributions that von Foerster’s constructivist cybernetics can make to cognitive science’s still limited understanding of the embodiment of cognition and “representation.” Relevance: The paper addresses the relevance of radical constructivism in general, and von Foerster’s work in particular, to modern embodied cognitive science and artificial intelligence research.

Key words: Cognition, cybernetics, artificial intelligence, reality.

This paper reviews some of the differences between notions of biological and robotic autonomy, and how these differences have been reflected in discussions of embodiment, grounding and other concepts in AI and autonomous robotics. Furthermore, the relations between homeostasis, emotion and embodied cognition are discussed as well as recent proposals to model their interplay in robots.

Upshot: Chemero provides a modern re-interpretation of Gibson’s ecological psychology and his affordance concept that is more coherent than the original and in line with antirepresentationalist, dynamical theories in embodied cognitive science. He argues for a radical embodied cognitive science, in which ecological and enactive approaches join forces against the more watered-down, mainstream embodied cognitive science that still maintains traditional commitments to representationalism and computationalism. He also defends a special version of realism, entity realism, which many constructivists might not find entirely convincing, but which is nevertheless more or less compatible with enactive theories of embodied cognition.

Open peer commentary on the article “Observing Environments” by Hugo F. Alrøe & Egon Noe. Upshot: Complementary to Alrøe and Noe’s discussion of constructivist notions of environment, world, etc., this commentary addresses the closely-related notion of agency in constructivist theories – in particular, the question of what would be required for artificial agency – and identifies open questions and fundamental disagreements among constructivist theorists.

Embodied cognition is a hot topic in both cognitive science and AI, despite the fact that there still is relatively little consensus regarding what exactly constitutes ‘embodiment’. While most embodied AI and cognitive robotics research views the body as the physical/sensorimotor interface that allows to ground computational cognitive processes in sensorimotor interactions with the environment, more biologically-based notions of embodied cognition emphasize the fundamental role that the living body – and more specifically its homeostatic/allostatic self-regulation – plays in grounding both sensorimotor interactions and embodied cognitive processes. Adopting the latter position – a multi-tiered affectively embodied view of cognition in living systems – it is further argued that modeling organisms as layered networks of bodily self-regulation mechanisms can make significant contributions to our scientific understanding of embodied cognition.

Key words: allostasis, cognitive systems, grounding, homeostasis, embodied ai, embodied cognition, emotion, intentionality, predictive regulation, representation

Emotion is characterized as (a) closely connected to embodied cognition, (b) grounded in homeostatic bodily regulation, and (c) a powerful organizational principle—affective modulation of behavioral and cognitive mechanisms—that is ‘useful’ in both biological brains and robotic cognitive architectures. We elaborate how emotion theories and models centered on core neurological structures in the mammalian brain, and inspired by embodied, dynamical, and enactive approaches in cognitive science, may impact on computational and robotic modeling. In light of the theoretical discussion, work in progress on the development of an embodied cognitive-affective architecture for robots is presented, incorporating aspects of the theories discussed.

Excerpt: Much research in cognitive science, and in particular artificial intelligence (AI) and artificial life (ALife), has since the mid-1980s been devoted to the study of so-called autonomous agents. These are typically robotic systems situated in some environment and interacting with it using sensors and motors. Such systems are often self-organizing in the sense that they artificially learn, develop, and evolve in interaction with their environments, typically using computational learning techniques, such as artificial neural networks or evolutionary algorithms. Due to the biological inspiration and motivation underlying much of this research (cf. Sharkey and Ziemke 1998), autonomous agents are often referred to as “artificial organisms”, “artificial life”, “animats” (short for “artificial animals”) (Wilson 1985), “creatures” (Brooks 1990), or “biorobots” (Ziemke and Sharkey 1998). These terms do not necessarily all mean exactly the same; some of them refer to physical robots only, whereas others include simple software simulations. But the terms all express the view that the mechanisms referred to are substantially different from conventional artifacts and that to some degree they are “life-like” in that they share some of the properties of living organisms. Throughout this article this class of systems will be referred to as “artificial organisms” or “autonomous agents/robots” interchangeably. \\The key issue addressed in this article concerns the semiotic status and relevance of such artificial organisms. The question is whether and to what extent they are autonomous and capable of semiosis. This is not straightforward since semiosis is often considered to necessarily involve living organisms. Morris (1946), for example, defines semiosis as “a signprocess, that is, a process in which something is a sign to some organism”. Similarly, Jakob von Uexküll considered signs to be “of prime importance in all aspects of life processes” (T. von Uexküll 1992), and made a clear distinction between organisms, which as autonomous subjects respond to signs according to their own specific energy, and inorganic mechanisms, which lack that energy, and thus remain heteronomous.

Key words: cognitive science, artificial intelligence, artificial life, semiotics, umwelt, mechanistic theories, self-organization