One of the most popular tacks taken to explain cognitive processes likens them to the operations of a digital computer. Indeed, the tasks for the cognitive scientist and the artificial intelligence scientist are often seen as indistinguishable: to understand how a machine or a brain “can store past information about the world and use that memory to abstract meaning from its percepts” (Solso, 1979, p. 425). The fact that there are machines that appear to do this, to varying degrees of success, is often taken to imply, almost by default, that cognition would have to embody the same steps in order to achieve the same results. In what folIows, we outline our objections to this attitude and briefly consider some alternatives.

This paper has two primary aims. The first is to provide an introductory discussion of hyperset theory and its usefulness for modeling complex systems. The second aim is to provide a hyperset analysis of several perspectives on autonomy: Robert Rosen’s metabolism-repair systems and his claim that living things are closed to efficient cause, Maturana and Varela’s autopoietic systems, and Kauffman’s cataytically closed systems. Consequences of the hyperset models for Rosen’s claim that autonomous systems have non-computable models are discussed.

Key words: Autonomy, Autopoiesis, Catalytic closure, Francisco Varela, Hyperset, Robert Rose

Open peer commentary on the article “Perception-Action Mutuality Obviates Mental Construction” by Martin Flament Fultot, Lin Nie & Claudia Carello. Upshot: We extend the authors’ arguments on direct perception, specificity, and foundational principles to concerns for theories of joint action. We argue for the usefulness of the affordance concept in an ecological theory of social interaction; highlighting linkages between theories of affordance-based behavior (control) and fundamental, physical principles.

A truly embodied-embedded approach to behavior promises a radical change in how scientists conceptualize cognitive agents (both biological and nonbiological) and how they proceed to understand the behavioral order of such agents, both empirically and theoretically. This chapter views that cashing in the promissory note requires that perceiving, acting and knowing be studied as emergent properties of an organism (O)–environment (E) system. The six principles described in the present chapter are proposed as an appropriate framework for that study. It presumes that the persistent application of the principles should enable cognitive and psychological science to repay the many loans of intelligence thus far accrued.

We examine Dubois’s (2003) distinction between weak anticipation and strong anticipation. Anticipation is weak if it arises from a model of the system via internal simulations. Anticipation is strong if it arises from the system itself via lawful regularities embedded in the system’s ordinary mode of functioning. The assumption of weak anticipation dominates cognitive science and neuroscience and in particular the study of perception and action. The assumption of strong anticipation, however, seems to be required by anticipation’s ubiquity. It is, for example, characteristic of homeostatic processes at the level of the organism, organs, and cells. We develop the formal distinction between strong and weak anticipation by elaboration of anticipating synchronization, a phenomenon arising from time delays in appropriately coupled dynamical systems. The elaboration is conducted in respect to (a) strictly physical systems, (b) the defining features of circadian rhythms, often viewed as paradigmatic of biological behavior based in internal models, (c) Pavlovian learning, and (d) forward models in motor control. We identify the common thread of strongly anticipatory systems and argue for its significance in furthering understanding of notions such as “internal”, “model” and “prediction”.

Key words: anticipation, synchronization, delayed feedback, homeostasis.

Background noise is the irregular variation across repeated measurements of human performance. Background noise remains after task and treatment effects are minimized. Background noise refers to intrinsic sources of variability, the intrinsic dynamics of mind and body, and the internal workings of a living being. Two experiments demonstrate l/f scaling (pink noise) in simple reaction times and speeded word naming times, which round out a catalog of laboratory task demonstrations that background noise is pink noise. Ubiquitous pink noise suggests processes of mind and body that change each other’s dynamics. Such interaction-dominant dynamics are found in systems that self-organize their behavior. Self-organization provides an unconventional perspective on cognition, but this perspective closely parallels a contemporary interdisciplinary view of living systems.