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.

Open peer commentary on the article “Foresight Rather than Hindsight? Future State Maximization As a Computational Interpretation of Heinz von Foerster’s Ethical Imperative” by Hannes Hornischer, Simon Plakolb, Georg Jäger & Manfred Füllsack. Abstract: As artificial intelligence (AI) continues to have a fundamental impact in our world and lives, a crucial need arises for integrating ethical and constructivist principles in the design of AI systems, and related computational thinking. We discuss aspects and examples of ethical and constructivist design of AI in the context of the target article, and especially in the domains of future-oriented ethical design and computing education.

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.

Key words: action-oriented perception, ape, architecture, artificial intelligence, automata theory, basal ganglia, brain theory, cerebellum, cerebral cortex, cognitive science, computational neuroscience, cybernetics, frog, hippocampus, human, language evolution, li

This chapter sketches an intellectual portrait of W. Ross Ashby’s thought from his earliest work on the mechanisms of intelligence in 1940 through the birth of what is now called artificial intelligence (AI), around 1956, and to the end of his career in 1972. It begins by examining his earliest published works on adaptation and equilibrium, and the conceptual structure of his notions of the mechanisms of control in biological systems. In particular, it assesses his conceptions of mechanism, equilibrium, stability, and the role of breakdown in achieving equilibrium. It then proceeds to his work on refining the concept of “intelligence,” on the possibility of the mechanical augmentation and amplification of human intelligence, and on how machines might be built that surpass human understanding in their capabilities. Finally, the chapter considers the significance of his philosophy and its role in cybernetic thought.

Key words: artificial intelligence, machine intelligence, equilibrium, human intelligence, cybernetic thought

The publication deals with the concept of self-reference across its multidisciplinary applications. The authors and themes scrutinized go from Plato and the Stoics to G. Günther and N. Luhmann; from paradoxes in Metamathematics to Artificial Intelligence.

The concept of agency is of crucial importance in cognitive science and artificial intelligence, and it is often used as an intuitive and rather uncontroversial term, in contrast to more abstract and theoretically heavily weighted terms such as intentionality, rationality, or mind. However, most of the available definitions of agency are too loose or unspecific to allow for a progressive scientific research program. They implicitly and unproblematically assume the features that characterize agents, thus obscuring the full potential and challenge of modeling agency. We identify three conditions that a system must meet in order to be considered as a genuine agent: (a) a system must define its own individuality, (b) it must be the active source of activity in its environment (interactional asymmetry), and (c) it must regulate this activity in relation to certain norms (normativity). We find that even minimal forms of proto-cellular systems can already provide a paradigmatic example of genuine agency. By abstracting away some specific details of minimal models of living agency we define the kind of organization that is capable of meeting the required conditions for agency (which is not restricted to living organisms). On this basis, we define agency as an autonomous organization that adaptively regulates its coupling with its environment and contributes to sustaining itself as a consequence. We find that spatiality and temporality are the two fundamental domains in which agency spans at different scales. We conclude by giving an outlook for the road that lies ahead in the pursuit of understanding, modeling, and synthesizing agents.

Key words: agency, individuality, interactional asymmetry, normativity, spatiality, temporality

The concept of agency is of crucial importance in cognitive science and artificial intelligence, and it is often used as an intuitive and rather uncontroversial term, in contrast to more abstract and theoretically heavy-weighted terms like “intentionality”, “rationality” or “mind”. However, most of the available definitions of agency are either too loose or unspecific to allow for a progressive scientific program. They implicitly and unproblematically assume the features that characterize agents, thus obscuring the full potential and challenge of modeling agency. We identify three conditions that a system must meet in order to be considered as a genuine agent: a) a system must define its own individuality, b) it must be the active source of activity in its environment (interactional asymmetry) and c) it must regulate this activity in relation to certain norms (normativity). We find that even minimal forms of proto-cellular systems can already provide a paradigmatic example of genuine agency. By abstracting away some specific details of minimal models of living agency we define the kind of organization that is capable to meet the required conditions for agency (which is not restricted to living organisms). On this basis, we define agency as an autonomous organization that adaptively regulates its coupling with its environment and contributes to sustaining itself as a consequence. We find that spatiality and temporality are the two fundamental domains in which agency spans at different scales. We conclude by giving an outlook to the road that lies ahead in the pursuit to understand, model and synthesize agents.

Upshot: University engineering qualifications are accredited according to various international accords that are perceived as a restrictive factor in curricula redesign. I argue that this may not be the case owing to the discipline-independent wide-ranging content that may populate the qualifications. Also, I point out that the educator’s teaching style is their choice and that educators may act as agents of change bringing ethical changes to their curricula. Finally, I question the role of the teacher and its future relevance in competition with artificial intelligence.

This paper describes a transdisciplinary theoretical-practical research, which address on the discussion about the possible applications of Multi-agent Systems, underlying the Maturana and Varela’s autopoietic concept considering the achievement of emergent results as heuristics to creativity. Autopoiesis (from the Greek “auto” which means “itself” and “poiesis” which means “creation”) describes the autonomous systems, able to self-reproduce and self-regulate, while iterating with the environment. In order to explore those concepts, we present Zer0, a game that invites the player to drift in a universe ruled by geometric shapes. Through interactions with other shapes, the player is able to evolve from a single line shape to more complex ones. Zer0 is a multi-agent system able to compose emergent music in real time. As interactions occur, chain reactions create the game soundtrack. There are two main agents involved: the player and the other shapes. While the player enjoys the ride, the other shapes are trying to interact with each other in order to expand their lifespan. The communication between agents is made through generated pulses, which are emitted by them and also serves as sonar, in order to perceive the environment.

Key words: Multi-agent systems, creativity, emergence, autopoiesis, artificial intelligence, interaction

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporate – everything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments.