Plant and animal species are information-processing entities of such complexity, integration, and adaptive competence that it may be scientifically fruitful to consider them intelligent. The possibility arises from the analogy between learning and evolution, and from recent developments in evolutionary science, psychology and cognitive science. Species are now described as spatiotemporally localized individuals in an expanded hierarchy of biological entities. Intentional and cognitive abilities are now ascribed to animal, human, and artificial intelligence systems that process information adaptively, and that manifest (...) problem-solving abilities. The structural and functional similarities between such systems and species are extensive, although they “are usually obscured by population-genetic metaphors that have nonetheless contributed much to our understanding of evolution.In this target article, I use Sewall Wright's notion of the “adaptive landscape” to compare the performances of evolving species to those of intelligent organisms. With regard to their adaptive achievements and the kinds of processes by which they are achieved, biological species compare very favorably to intelligent animals by virtue of interactions between populations and their environments, between ontogeny and phylogeny, and between natural, interdemic, organic, and species selection. Addressing the question of whether species are intelligent could help to refine our ideas about species, evolution, and intelligence, and could open new lines of empirical and theoretical inquiry in many disciplines. (shrink)

Standard semantic information processing models—information in; information processed; information out —lend themselves to standard models of the functioning of the brain in terms, e.g., of threshold-switch neurons connected via classical synapses. That is, in terms of sophisticated descendants of McCulloch and Pitts models. I argue that both the cognition and the brain sides of this framework are incorrect: cognition and thought are not constituted as forms of semantic information processing, and the brain does not function in terms of passive input (...) processing units organized as neural nets. An alternative framework is developed that models cognition and thought not in terms of semantic information processing, and, correspondingly, models brain functional processes also not in terms of semantic information processing. As alternative to such models: I outline a pragmatist oriented, interaction based, model of representation; derive from this model a fundamental framework of constraints on how the brain must function; show that such a framework is in fact found in the brain, and develop the outlines of a broader model of how mental processes can be realized within this alternative framework. Part I of this discussion focuses on some criticisms of standard modeling frameworks for representation and cognition, and outlines an alternative interactivist, pragmatist oriented, model. In part II, the focus is on the fact that the brain does not, in fact, function in accordance with standard passive input processing models—e.g., information processing models. Instead, there are multiple endogenously active processes at multiple spatial and temporal scales across multiple kinds of cells. A micro-functional model that accounts for, and even predicts, these multi-scale phenomena in generating emergent representation and cognition is outlined. That is, I argue that the interactivist model of representation outlined offers constraints on how the brain should function that are in fact empirically found, and, in reverse, that the multifarious details of brain functioning entail the pragmatist representational model—a very strong interrelationship. In the sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the model presented here: sometimes called the predictive brain approach. (shrink)

SummaryThis paper explicates a Constructivist Epistemology which underlies cybernetic models of perceiving and knowing. We focus on the recent work of W. T. Powers . Powers' model consists of hierarchially arranged negative feedback systems, is based on the claim that living organisms behave to control perceptions, and thus suggests that organisms construct their experiential world. We argue that this provides a basis for a modified scientific scepticism, a scepticism with a positive dimension gained by adding the notion of cognitive construction. (...) From this perspective, knowing and perceiving pertain to the construction of invariances in the living organism's experience.RésuméDans cet essai, nous exposons une épistémologie constructivistc qui sert de base pour des modèles cybernétiques de la perception et de la connaissancc. Nous nous référonts à l'œuvre de W. T. Powers qui a propose un modèle constitué par un arrangement hiérarchique de boucles rétroactives en partant de l'idée que tout comportement a pour but de contrôler les perceptions. Ce modèle suggère que le monde expérientiel est le produit d'une activité constructive. Nous défendons la thèse que cette orientation peut fournir le fondement d'un scepticisme scientifique qui acquiert un aspect positif par la notion de construction cognitive. De ce point de vue, connaissance et perception sont des activités qui construisent des invariances dans l'expérience d'un organisme.ZusammenfassungIn der vorliegenden Arbeit wird eine konstruktivistische Erkenntnistheorie entwickelt, die ihrerseits gewissen kybernetischen Modeller) der Wahrnehmurtg und Er‐kenntnis zugrundeliegt. Wir beziehen uns auf die Untersuchungen von W. T. Powers , dessen Modell aus hierarchisch angeordneten Rückkopplungssystemen besteht und auf der Annahme be‐ruht, dass das Verhalten von Lebewesen der Regelung von Wahrnehmungcn dicnt. Powers legt deshalb die Hypothese nahe, dass Organismen ihre Erlebenswelt konstru‐iren. Wir vertreten die Ansicht, dass diese die Grundlage für einen neuen wisscnschaftli‐chen Skeptizismus liefert, der auf Grund des Begriffes der kognitiven Konstruktion eine positive Dimension gewinnt. Von diesem Gesichtspunkt aus betrachtet betreffen Wissen und Wahrnehmung den aktiven Aufbau von Konstanten in der Erlebenswelt des Orga‐nismus. (shrink)

The research reported in this document has been sponsored by the Air Force Office of Scientific Research, OAR, under Contract AF61 ‐640 with the European Office of Aerospace Research, United States Air Force; by the Aeronautical Systems Division of the Air Force Systems Command, United States Air Force, through the European Office of the Office of Aerospace Research, under Contract AF61‐402, and by the US Department of the Army, through its European Research Office, under Contract No. DA‐91‐591‐EUC‐3216.

The Cartesian concept of nature, which has determined modern thinking until the present time, has become obsolete. It shall be shown that Hegel's objective-idealistic conception of nature discloses, in comparison to that of Descartes, new perspectives for the comprehension of nature and that this, in turn, results in possibilities of actualizing Hegel's philosophy of nature. If the argumentation concerning philosophy of nature is intended to catch up with the concrete Being-of-nature and to meet it in its concretion, then this is (...) impossible for the finite spirit in a strictly a priori sense – this is the thesis supported here which is not at all close to Hegel. As the argumentation rather has to consider the conditions of realization concerning the Being-of-nature, too, it is compelled to take up empirical elements – concerning the organism, for instance, system-theoretical aspects, physical and chemical features of the nervous system, etc. With that, on the one hand, empirical-scientific premises are assumed (e.g. the lawlikeness of nature), which on the other hand become (now close to Hegel) possibly able to be founded in the frame of a Hegelian-idealistic conception. In this sense, a double strategy of empirical-scientific concretization and objective-idealistic foundation is followed up, which represents the methodical basic principle of the developed considerations. In the course of the undertaking, the main aspects of the whole Hegelian design concerning the philosophy of nature are considered – space and time, mass and motion, force and law of nature, the organism, the pro-blem of evolution, psychic being – as well as Hegel's basic thesis concerning the philosophy of nature, that therein a tendency toward coherence and idealization manifests itself in the sense of a (categorically) gradually rising succession of nature: from the separateness of space to the ideality of sensation. In the sense of the double strategy of concretization and foundation it is shown that on the one hand possibilities of philosophical penetration concerning actual empirical-scientific results are opened, and on the other hand – in turn – a re-interpretation of Hegel's theorem on the basis of physical, evolution-theoretical and system-theoretical argumentation also becomes possible. In this mutual crossing-over and elucidation of empirical and Hegelian argumentation not only do perspectives of a new comprehension of nature become visible, but also, at the same time – as an essential consequence of this methodical principle – thoughts on the possibilities of actualizing Hegel's philosophy of nature. (shrink)

At the heart of evolutionary theory lays the notion of replication. Unfortunately, this notion is far less exact than the weight of its importance. In this paper, it is argued that replication always involves coding. Furthermore, when a theory of evolution is built on replication based on coding, a unifying and coherent picture arises that sheds new light on some of the controversies and open questions in contemporary biology, such as what are the roles of phylogeny and ontogeny in evolution, (...) and how to characterize and explain the increase of biological complexity. (shrink)

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a (...) categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. (shrink)

Consciousness and experience, William G. Lycan. Cambridge, MA: MIT Press, 1996. ISBN 0–262–12197–2 (hc)Mind as motion: explorations in the dynamics of cognition, Robert Port & Timothy Van Gelder (Eds). Cambridge, MA: MIT/Bradford, 1995. ISBN 0–262–16150–8Perception, Kathleen Akins (Ed.). New York: Oxford University Press, 1996. ISBN 0–19–508461 (hbk); 0–19–508462–4 (pbk)Context and consciousness, B. Nardi (Ed.). Cambridge, MA: MIT Press, 1996. ISBN: 0–262–14058–6Catching ourselves in the act, Horst Hendriks‐Jansen. Cambridge, MA: MIT Press, 1996. ISBN 0–262–08246–2The search for mind. A new foundation for (...) cognitive science, Sean O'Nuallain. Norwood, NJ: Ablex, 1995Mindblindness: an essay on autism and theory of mind, Simon Baron‐Cohen. Cambridge, MA: MIT Press, 1995. ISBN 0–262–02384–9. (shrink)

The paper is a commentary on the target article by Christine A. Skarda & Walter J. Freeman, “How brains make chaos in order to make sense of the world”, in the same issue of the journal, pp.161–195. -/- I confine my comments largely to some philosophical claims that Skarda & Freeman make and to the relationship of their model to connectionism. Some of the comments hinge on what symbols are and how they might sit in neural systems.

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models.Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. Parallel connectionist memory and linguistic processes are hypothesized to give rise to processes that are describable at a higher level as sequential rule application. At the lower level, computation has the character of massively parallel satisfaction of soft numerical constraints; at the higher level, this can lead to competence characterizable by hard rules. Performance will typically deviate from this competence since behavior is achieved not by interpreting hard rules but by satisfying soft constraints. The result is a picture in which traditional and connectionist theoretical constructs collaborate intimately to provide an understanding of cognition. (shrink)

Human behavior is the joint product of (i) contingencies of survival responsible for natural selection, and (ii) contingencies of reinforcement responsible for the repertoires of individuals, including (iii) the special contingencies maintained by an evolved social environment. Selection by consequences is a causal mode found only in living things, or in machines made by living things. It was first recognized in natural selection: Reproduction, a first consequence, led to the evolution of cells, organs, and organisms reproducing themselves under increasingly diverse (...) conditions. The behavior functioned well, however, only under conditions similar to those under which it was selected.Reproduction under a wider range of consequences became possible with the evolution of processes through which organisms acquired behavior appropriate to novel environments. One of these, operant conditioning, is a second kind of selection by consequences: New responses could be strengthened by events which followed them. When the selecting consequences are the same, operant conditioning and natural selection work together redundantly. But because a species which quickly acquires behavior appropriate to an environment has less need for an innate repertoire, operant conditioning could replace as well as supplement the natural selection of behavior.Social behavior is within easy range of natural selection, because other members are one of the most stable features of the environment of a species. The human species presumably became more social when its vocal musculature came under operant control. Verbal behavior greatly increased the importance of a third kind of selection by consequences, the evolution of social environments or cultures. The effect on the group, and not the reinforcing consequences for individual members, is responsible for the evolution of culture. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. Parallel connectionist memory and linguistic processes are hypothesized to give rise to processes that are describable at a higher level as sequential rule application. At the lower level, computation has the character of massively parallel satisfaction of soft numerical constraints; at the higher level, this can lead to competence characterizable by hard rules. Performance will typically deviate from this competence since behavior is achieved not by interpreting hard rules but by satisfying soft constraints. The result is a picture in which traditional and connectionist theoretical constructs collaborate intimately to provide an understanding of cognition. (shrink)

It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both the behaviour of the (...) network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)

We present a novel methodology for building humanlike artificially intelligent systems. We take as a model the only existing systems which are universally accepted as intelligent: humans. We emphasize building intelligent systems which are not masters of a single domain, but, like humans, are adept at performing a variety of complex tasks in the real world. Using evidence from cognitive science and neuroscience, we suggest four alternative essences of intelligence to those held by classical AI. These are the parallel themes (...) of development, social interaction, embodiment, and integration. Following a methodology based on these themes, we have built a physical humanoid robot. In this paper we present our methodology and the insights it affords for facilitating learning, simplifying the computation underlying rich behavior, and building systems that can scale to more complex tasks in more challenging environments. (shrink)

Brain functions are stochastic processes without intentionality whereas mind emerges from brain functions as a Hegelian “change from quantity”, that is, on the order of 1012 profusely interconnected neurons, “into a new quality”: the collective phenomenon of the brain's self-experience. This self-referential and self-observing quality we have in mind is capable of (recursively) observing its self-observations, i.e., interpreting change that is meaningful in relation to itself. The notion of self-interpretation embodies the idea of a “hermeneutic circle”, that is, (in interpretation (...) theory) the treatment of the whole in relation to its parts. (shrink)

Introductory Abstract Philosophers of science, in the course of making a sharp distinction between the tasks of the philosopher and those of the scientist, have pointed to the possibility of an empirical science of induction. A comparative psychology of knowledge processes is offered as one aspect of this potential enterprise. From fragments of such a psychology, methodological suggestions are drawn relevant to several chronic problems in the social sciences, including the publication of negative results from novel explorations, the operational diagnosis (...) of dispositions, the status of aggregates of persons as social entities, and the validation of psychological tests. (shrink)

Modern knowledge of servo systems and computing machines makes it possible to specify a circuit that can and will induce the rules and winning moves in a game like chess when they are given only ostensibly, that is, by playing against opponents who quit when illegal or losing moves are made. Such circuits enjoy a value social in the sense that it is shared by the players.La connaissance moderne des servomécanismes et des machines à calculer permet de concevoir un circuit (...) qui pourra suivre des règles et décider les coups décisifs dans un jeu comme le jeu d'échecs tout au moins quand les coups sont joués de faÇon apparente, c'est-à-dire contre des adversaires qui abandonneront dans le cas de coups irréguliers ou de coups absurdes.De tels circuits possèdent une „valeur” sociale dans la mesure où elle est partagée par les autres joueurs.Moderne Kenntnissen im Gebiete von Folgegeraeten und Rechenmaschinen ermoeglichen es einen elektrischen Kreis aufzuwerfen, der die Regeln und gewinnbringende Zuege eines Spieles wie Schach induktiv erfassen kann und wird, wenn diese Regeln und Zuege nur ostensiv gegeben sind; d.h. indem mit Gegnern gespielt wird, die das Spiel einstellen sobald regelwidrige oder verlustbringende Zuege gemacht werden. Solche Kreise schaffen demnach einen Wert, der gesellschaftlich in dem Sinn ist, dass er auch von den Mitspielern geteilt wird. (shrink)

No doubt, we human beings often think about objects, remember facts and imagine events.

Cybernetics for the 21st Century Vol.1 is dedicated to the epistemological reconstruction of cybernetics, consisting of a series of historical and critical reflections on the subject – which according to Martin Heidegger marked the completion of Western metaphysics. In this anthology, historians, philosophers, sociologists and media studies scholars explore the history of cybernetics from Leibniz to artificial intelligence and machine learning, as well as the development of twentieth-century cybernetics in various geographical regions in the world, from the USA to the (...) Soviet Union, Latin America, France, Poland, China and Japan. The reconstruction shows the various paths of cybernetics and their socio-political implications, which remain unfamiliar to us today. It reveals more than what we thought we knew – and yet we hardly know – and allows us to understand where we are and to reflect on the future of technology, ecology and planetary politics. (shrink)

The term ‘information’ is used extensively in biology, cognitive science and the philosophy of consciousness in relation to the concepts of ‘meaning’ and ‘causation’. While ‘information’ is a term that serves a useful purpose in specific disciplines, there is much to the concept that is problematic. Part 1 is a critique of the stance that information is an independently existing entity. On this view, and in biological contexts, systems transmit, acquire, assimilate, decode and manipulate it, and in so doing, generate (...) meaning. I provide a detailed proposal in Part 2 that supports the claim that it is the dynamic form of a system that qualifies the informational nature of meaningful interactive engagement, that is, that information is dependent on dynamic form rather than that it exists independently. In Part 3, I reflect on the importance of the distinction between the independent and dependent stances by looking specifically at the implications for how we might better interpret causation and emergence. (shrink)

Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work of Gilbert (...) Simondon, with its critique of Norbert Wiener‘s first-order cybernetics, offers a precursor to the conception of second-order cybernetics (as endorsed byFrancisco Varela, Humberto Maturana, and Ricardo B. Uribe) and, specifically, its autopoietic treatment of information. It has been argued by those such as Frank Pasquale that neuro-inferential deep learning systems premised on predictive patterning, suchas AlphaGo Zero, have a veiled logic and, thus, are ̳black boxes‘. In detailing a philosophical-historical approach to demystify predictive patterning/processing and the logic of such deep learning algorithms, this paper attempts to shine a light on such systems and their inner workingsàla Simondon. (shrink)

The present investigation brings into view the philosophy of nature of German Idealism, a philosophical movement which emerged around the beginning of the nineteenth century. German Idealism appro- priated certain motivations of the Kantian philosophy and developed them further in a "speculative" manner (Engelhardt 1972, 1976, 2002). This powerful philosophical movement, associated above all with the names of Fichte, Schelling and Hegel - and moreover having nothing whatsoever to do with the "subjective idealism" of George Berkeley - was replaced by (...) philosophical positions designated roughly as metaphysics of the will, Marxism, life-philosophy, phenomenology and existentialism, as well as positivism, empiricism, philosophy of science, the linguistic turn, and analytic philosophy. These philosophical positions more or less still shape us today. German Idealism amounts to a virtual intellectual-historical antithesis to these movements and thus presents itself in retrospect as a striking alternative. The basis of Idealism - in its various respective forms - is the ideal <Ideelle>, and thus the opposite of that which is real. It continually takes as its task explaining the real in terms of the ideal, and this is especially true of the Idealists' philosophy of nature.' Is this a hopeless undertaking? Does Idealism not lack an empirical basis? Can one secure any solid ground whatsoever in the ether of the ideal? In what follows, I explain how, more than anyone else, Schelling and Hegel sought to handle this problem and to cope with it. By way of anticipation, a clear preference for the Hegelian philosophy of nature will emerge in what follows, a preference which may come as some surprise considering how much controversy has surrounded the significance of that view. The project of renewing a thoroughgoing philosophy of nature can meaningfully begin here. (shrink)

Action-based theories of cognition place primary emphasis upon the role that agent-environment coupling plays in the emergence of psychological states. Prima facie, mental imagery seems to present a problem for some of these theories because it is understood to be stimulus-absent and thus thought to be decoupled from the environment. However, mental imagery is much more multifaceted than this “naïve” view suggests. Focusing on a particular kind of imagery, comparative mental imagery generation, this paper demonstrates that although such imagery is (...) stimulus-absent, it is also stimulus-sensitive. Exhibiting stimulus-sensitivity is sufficient for a process to qualify as coupled to the environment. The notion of variant coupling is explicated as the coupling of a cognizer’s perceptual system to variant environmental information. By demarcating the categories of stimulus-absent and stimulus-sensitive cognition, and variant and invariant coupling, this paper expands the conceptual apparatus of action-based theories, suggesting not only a way to address the problem that comparative mental imagery generation presents, but perhaps a way to account for other forms of imagery too. (shrink)

Digital computers carry out algorithms coded in high level programs. These abstract entities determine what happens at the physical level: they control whether electrons flow through specific transistors at specific times or not, entailing downward causation in both the logical and implementation hierarchies. This paper explores how this is possible in the light of the alleged causal completeness of physics at the bottom level, and highlights the mechanism that enables strong emergence (the manifest causal effectiveness of application programs) to occur. (...) Although synchronic emergence of higher levels from lower levels is manifestly true, diachronic emergence is generically not the case; indeed we give specific examples where it cannot occur because of the causal effectiveness of higher level variables. (shrink)

The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also (...) unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. (shrink)