Excerpt: Both behaviorism and constructivism stem from centuries of philosophical musing concerning the nature of reality, our perceptions of reality, and even whether reality, as we perceive it, actually exists. The first and third of these issues are perhaps more than we might want to discuss here, but the second seems fair game. It allows us to progress from philosophy to experimental psychology and, finally, to what we might say about one aspect of constructivist thinking, namely, the situation of learning in authentic experiences. This chapter suggests that constructivist prescriptions for situated learning may be derived from our philosophical roots, empirical findings from experimental psychology, and experiences with situated-learning environments that rely on simulations. Much of the empirical support that is reported here derives from the use of simulation in military training, but let’s start with some philosophers.

Context: W. R. Ashby’s work on homeostasis as the basic mechanism underlying all kinds of physiological as well as cognitive functions has aroused renewed interest in cognitive science and related disciplines. Researchers have successfully incorporated some of Ashby’s technical results, such as ultrastability, into modern frameworks (e.g., CTRNN networks). Problem: The recovery of Ashby’s technical contributions has left in the background Ashby’s far more controversial non-technical views, according to which homeostatic adaptation to the environment governs all aspects of all forms of life. This thesis entails that life is fundamentally “heteronomous” and it is conceptually at odds with the autopoiesis framework adopted by Ashby’s recent defenders as well as with the primacy of autonomy in human life that most of the Western philosophical tradition upholds. The paper argues that the use of computer simulations focused on the more conceptual aspects of Ashby’s thought may help us recover, extend and consequently assess an overall view of life as heteronomy. Method: The paper discusses some computer simulations of Ashby’s original electro-mechanical device (the homeostat) that implement his techniques (double-feedback loops and random parameter-switching). Results: First simulation results show that even though Ashby’s claims about homeostatic adaptivity need to be slightly weakened, his overall results are confirmed, thereby suggesting that an extension to virtual robots engaged in minimal cognitive tasks may be successful. Implications: The paper shows that a fuller incorporation of Ashby’s original results into recent cognitive science research may trigger a philosophical and technical reevaluation of the traditional distinction between heteronomous and autonomous behavior. Constructivist content: The research outlined in the paper supports an extended constructionist perspective in which agency as autonomy plays a more limited role.

Key words: Second-order cybernetics, autonomy and agency, general homeostasis thesis, W. R. Ashby, homeostat, concept simulation

Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: Scott and Bansal’s assessment of the limitations of their work relies on a concept of simulation that I find problematic. It assumes that the ultimate goal of a model is a replication of the phenomena it applies, whereas a limited model produces only simulations. I argue that this position leads to unfortunate epistemological results, and it ends up assigning an unduly exclusive role to the study of the biochemical substrate of cognition.

The branch of semiotics called semantics deals with the relation between meanings and representations, widely known as the symbol grounding problem. The other branches of semiotics, syntactics which deals with symbol–symbol relations as in a dictionary, and pragmatics which deals with symbol-action paradigms as in traffic signs, are well done by computers, but semantics has eluded computer simulation. In my view, this is because computer programmers have neglected that aspect of Shannon’s definition by which information has no meaning; computers process information, whereas brains create meaning. Brains obtain information about the world through the consequences of their own embodied actions. The information thus obtained is used in constructing meaning and is then discarded. One kind of information in the world consists of representations made by other brains for social communication. Computers use representations for information processing and symbol manipulation. However, brains have no internal representations. They deploy dynamic neural operators in the form of activity patterns, which constitute and implement meaning but not information, so that the problem of symbol grounding does not arise. Brains construct external representations in the form of material objects or movements as their means for expressing their internal states of meaning, such as words, books, paintings, and music, as well as facial expressions and gestures in animals and humans, but even though those material objects are made with the intent to elicit meaning in other brains, they have no meanings in themselves and do not carry meanings as if they were buckets or placards. Meanings can only exist in brains, because each meaning expresses the entire history and experience of an individual. It is an activity pattern that occupies the entire available brain, constituting a location in the intentional structure of a brain. It is the limited sharing of meanings between brains for social purposes that requires reciprocal exchanges of representations, each presentation by a transmitting brain inducing the construction of new meaning in the receiving brain. EEG data indicate that neural patterns of meanings in each brain occur in trajectories of discrete steps, which are demarcated by first-order state transitions that enable formation of spatiotemporal patterns of spatially coherent oscillations. Amplitude modulation is the mode of expressing meanings. These wave packets do not represent external objects; they embody and implement the meanings of objects for each individual, in terms of what they portend for the future of that individual, and what that individual should do with and about them.

There are some signs that a resurgence of interest in modeling constitutive autonomy is underway. This paper contributes to this recent development by exploring the possibility of using evolutionary robotics, traditionally only used as a generative mechanism for the study of embodied-embedded cognitive systems, to generate simulation models of constitutively autonomous systems. Such systems, which are autonomous in the sense that they self-constitute an identity under precarious conditions, have so far been elusive. The challenges and opportunities involved in such an endeavor are explicated in terms of a concrete model. While we conclude that this model fails to fully satisfy all the organizational criteria that are required for constitutive autonomy, it nevertheless serves to illustrate that evolutionary robotics at least has the potential to become a valuable tool for generating such models.

Key words: artificial life, autopoiesis, evolutionary robotics, autonomy.

There is a growing realization in cognitive science that a theory of embodied intersubjectivity is needed to better account for social cognition. We highlight some challenges that must be addressed by attempts to interpret ‘simulation theory’ in terms of embodiment, and argue for an alternative approach that integrates phenomenology and dynamical systems theory in a mutually informing manner. Instead of ‘simulation’ we put forward the concept of the ‘extended body’, an enactive and phenomenological notion that emphasizes the socially mediated nature of embodiment. To illustrate the explanatory potential of this approach, we replicate an agent-based model of embodied social interaction. An analysis of the model demonstrates that the extended body can be explained in terms of mutual dynamical entanglement: inter-bodily resonance between individuals can give rise to self-sustaining interaction patterns that go beyond the behavioral capacities of isolated individuals by modulating their intra-bodily conditions of behavior generation.

Key words: Enaction, Embodied intersubjectivity, Dynamical systems theory, Social cognition

The invention of the computer has revolutionized science. With respect to finding the essential structures of life, for example, it has enabled scientists not only to investigate empirical examples, but also to create and study novel hypothetical variations by means of simulation: ‘life as it could be’. We argue that this kind of research in the field of artificial life, namely the specification, implementation and evaluation of artificial systems, is akin to Husserl’s method of free imaginative variation as applied to the specific regional ontology of biology. Thus, at a time when the clarification of the essence of our biological embodiment is of growing interest for phenomenology, we suggest that artificial life should be seen as a method of externalizing some of the insurmountable complexity of imaginatively varying the phenomenon of life.

The history of realism is the best argument for constructivism, but that is only the start of constructivism’s troubles! Although constructivism is typically seen as existing within the human sciences, the perils that await constructivism have already been foreshadowed in the history of the natural sciences. After surveying the various instabilities inherent in the realist position, I consider the natural science whose self-understanding has been most consistently constructivist: chemistry. After drawing some lessons from chemistry’s ill-fated attempt at socio-epistemic prominence earlier this century, I then examine recent constructivist efforts to avoid the ‘context-captivity’ that befell chemistry. However, these depend too much on the ‘normal science’ image of inquiry that constructivism is supposedly designed to subvert. Nevertheless, a precedent for this position may be found in rhetoric’s historical retreat from political involvement to the pursuit of ‘interpretation’. Next, I argue that one way of repoliticizing constructivism is to consider alternative social formations within which constructivist projects can be pursued. Surprisingly, this sense of ‘reflexivity’ has been under-represented in the constructivist literature. Social movements appear to be an especially good alternative to, say, disciplinary paradigms, for reasons that I go on to explain. Finally, the entire discussion is epitomized by contrasting ‘Right’ and ‘Left’ constructivisms according to the features of realism that constructivists have felt worthy of simulation.

Problem: Can communication emerge from the interaction of “self-referentially closed systems,” conceived as operating solely on the base of the “internal” output of their onboard means? Or in terms of philosophical conceptions: can communication emerge without (“outward” directed) “intention” or “will to be understood”? Method: Multi-agent simulation based on a conceptual analysis of the theory of social systems as suggested by Niklas Luhmann. Results: Agents that co-evolutionarily aggregate probabilities on how to cope with their environment can structurally couple and generate a form of “eigenbehavior” that retrospectively (i.e., by an observer) might be interpreted as communication. Implications: The “intention” or the “will to be understood,” as prominently claimed to be indispensable in communication by theoreticians such as Jürgen Habermas, can be seen as a retrospective ascription to an emergent property of complex interaction. Constructivist content: The paper attempts to base constructivist reasoning on data generated in simulations.

Key words: Communication, information, contingency, structural coupling, intentionality, observer dependency, multi-agent simulation.

Problem: Is constructivism contradicted by the reductionist determinism inherent in digital computation? Method: Review of examples from dynamical systems sciences, agent-based modeling and artificial intelligence. Results: Recent scientific insights seem to give reason to consider constructivism in line with what computation is adding to our knowledge of interacting dynamics and the functioning of our brains. Implications: Constructivism is not necessarily contradictory to digital computation, in particular to computer-based modeling and simulation. Constructivist content: When viewed through the lens of computation, in many of its aspects constructivism seems in line with what currently is held to be valid in science.

Key words: Computation, observation, emergence, downward causation, simulation, modeling, artificial intelligence, robotics