While structured as an autobiography, this memoir exemplifies ways in which classic contributions to cybernetics (e.g., by Wiener, McCulloch & Pitts, and von Neumann) have fed into a diversity of current research areas, including the mathematical theory of systems and computation, artificial intelligence and robotics, computational neuroscience, linguistics, and cognitive science. The challenges of brain theory receive special emphasis. Action-oriented perception and schema theory complement neural network modeling in analyzing cerebral cortex, cerebellum, hippocampus, and basal ganglia. Comparative studies of frog, rat, monkey, ape and human not only deepen insights into the human brain but also ground an EvoDevoSocio view of “how the brain got language.” The rapprochement between neuroscience and architecture provides a recent challenge. The essay also assesses some of the social and theological implications of this broad perspective.
This article considers W. Ross Ashby’s ideas on the nature of embodied minds, as articulated in the last five years of his career. In particular, it attempts to connect his ideas to later work by others in robotics, perception and consciousness. While it is difficult to measure his direct influence on this work, the conceptual links are deep. Moreover, Ashby provides a comprehensive view of the embodied mind, which connects these areas. It concludes that the contemporary fields of situated robotics, ecological perception, and the neural mechanisms of consciousness might all benefit from a reconsideration of Ashby’s later writings.
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.
Excerpt: In their introduction to the first International Workshop on Epigenetic Robotics, Zlatev and Balkenius (2001) suggested the term epigenetic robotics to denote a new field of research resulting from the mutual rapprochement of developmental psychology and robotics, with a focus on the prolonged epigenetic developmental process through which increasingly more complex cognitive structures emerge in the system as a result of interactions with the physical and social environment.
Bettoni M. C. (2018) Diving Deeply into Radical Constructivism. Constructivist Foundations 13(2): 270–272. https://cepa.info/4619
Open peer commentary on the article “Applying Radical Constructivism to Machine Learning: A Pilot Study in Assistive Robotics” by Markus Nowak, Claudio Castellini & Carlo Massironi. Upshot: Applying radical constructivism to machine learning is a challenge that requires us to dive very deeply into its theory of knowing and learning. We need to clarify its fundamental concepts, if possible, in operational terms. This commentary aims at outlining how this kind of clarification could look in the case of 3 such concepts: (a) the construction of experiential reality; (b) learning as a constructive activity; (c) the viability of conceptual structures.
Bishop J. M. & Nasuto S. J. (2005) Second-order cybernetics and enactive perception. Kybernetes 34(9/10): 1309–1320. https://cepa.info/835
Purpose: To present an account of cognition integrating second-order cybernetics (SOC) together with enactive perception and dynamic systems theory. Methodology – The paper presents a brief critique of classical models of cognition then outlines how integration of SOC, enactive perception and dynamic systems theory can overcome some weaknesses of the classical paradigm. Findings: Presents the critique of evolutionary robotics showing how the issues of teleology and autonomy are left unresolved by this paradigm although their solution ﬁts within the proposed framework. Implications: The paper highlights the importance of genuine autonomy in the development of artiﬁcial cognitive systems. It sets out a framework within which the robotic research of cognitive systems could succeed. Practical implications: There are no immediate practical implications but see research implications. Originality/value – It joins the discussion on the fundamental nature of cognitive systems and emphasises the importance of autonomy and embodiment. Relevance: This paper draws explicit links between second order cybernetics, enactivism and dynamic systems accounts of cognition.
Cariani P. (1993) To evolve an ear: Epistemological implications of Gordon Pask’s electrochemical devices. Systems Research 10(3): 19–33. https://cepa.info/2836
In the late 1950's Gordon Pask constructed several electrochemical devices having emergent sensory capabilities. These control systems possessed the ability to adaptively construct their own sensors, thereby choosing the relationship between their internal states and the world at large. Devices were built that evolved de novo sensitivity to sound or magnetic fields. Pask’s devices have far-reaching implications for artificial intelligence, self-constructing devices, theories of observers and epistemically-autonomous agents, theories of functional emergence, machine creativity, and the limits of contemporary machine learning paradigms.
The work of physicist and theoretical biologist Howard Pattee has focused on the roles that symbols and dynamics play in biological systems. Symbols, as discrete functional switching-states, are seen at the heart of all biological systems in the form of genetic codes, and at the core of all neural systems in the form of informational mechanisms that switch behavior. They also appear in one form or another in all epistemic systems, from informational processes embedded in primitive organisms to individual human beings to public scientific models. Over its course, Pattee’s work has explored (1) the physical basis of informational functions (dynamical vs. rule-based descriptions, switching mechanisms, memory, symbols), (2) the functional organization of the observer (measurement, computation), (3) the means by which information can be embedded in biological organisms for purposes of self-construction and representation (as codes, modeling relations, memory, symbols), and (4) the processes by which new structures and functions can emerge over time. We discuss how these concepts can be applied to a high-level understanding of the brain. Biological organisms constantly reproduce themselves as well as their relations with their environs. The brain similarly can be seen as a self-producing, self-regenerating neural signaling system and as an adaptive informational system that interacts with its surrounds in order to steer behavior.
Problem: How can radical constructivism gain wider recognition and acceptance? Method: Based on informal direct observation of other social and intellectual movements, the social and psychological dynamics and organizational imperatives of radical constructivism as an intellectual movement are discussed. Results: Various means of structuring the movement in order to gain wider acceptance are proposed. Implications: We hope that the paper has value in helping the radical constructivism movement evaluate where it has been and where it might go in terms of wider social recognition and acceptance.
Open peer commentary on the article “Applying Radical Constructivism to Machine Learning: A Pilot Study in Assistive Robotics” by Markus Nowak, Claudio Castellini & Carlo Massironi. Upshot: The stripped-down experimental setup may be missing important sensory proprioceptive and tactile observables that may well be crucial for designing useful, effective, and flexible general-purpose motor prosthetic devices. Because trainable machines cannot by themselves add new observables, designers must foresee which ones are needed.