This article deals with the notion of reality. During the last twenty years, public discourse in western societies has identified the opposition between the real and the virtual as one of the cultural key questions. Taking concrete examples as a point of departure, the paper investigates the semantics of the polysemic terms virtual and real. A semiotic model of the relation between (human) organisms, concepts and signs is used in order to demonstrate that the virtual cannot be adequately described as something opposed to reality, but must be seen as an indispensable part of it. The way in which organisms constitute reality is discussed in the light of the basic cognitive operations of categorization and the formation of conceptual relations, and also of their linguistic counterparts. The apparent conflict between the real and the virtual, which has led many critics to develop apocalyptic visions of the end of civilization, is, in fact, a phantom, product of an outdated theory of semantics.

Key words: coherence, communication, culture, semantics, semiotics, virtual reality

In the context of the question of the emergence of mind in evolution the present paper argues that the concept of linguistic motivation, through the theory of embodiment in cognitive semantics, can be connected with the concept of motivation in ethology. This connection is established through Lakoff and Johnson’s embodied cognitive semantics on the one hand and on the other hand through the theory of biosemiotics. The biosemiotics used is based on C. S. Peirce´s semiotics and the work of J. von Uexkull. Motivation will in this context be understood as a decisive factor in determining which kind of interpretant a living system constructs when perturbed by a significant disturbance in its signification sphere. From this basis the concept of sign stimuli in Ethology, based on the concept of innate release response mechanism (IRM,) is paralleled with the concept of embodied metaphorical categorization based on the concept of idealized cognitive models (ICM). It is realized that we are dealing with motivation on two different levels, that of the linguistic and that of the perceptual-behavioral level. The connection is made through pragmatic language and sign theory viewing language as getting its meaning through language games integrated in cultural life forms and animals signs to get their meaning through sign games and natural life forms. Further connection is made through the common insight of the significant role of embodiment to create signification through the construction of a signification sphere. The later concept is a Peircian biosemiotic conceptualization of von Uexkull’s orginal Umwelt concept.

According to the sensorimotor approach, perception is a form of embodied know-how, constituted by lawful regularities in the sensorimotor flow or in sensorimotor contingencies (SMCs) in an active and situated agent. Despite the attention that this approach has attracted, there have been few attempts to define its core concepts formally. In this paper, we examine the idea of SMCs and argue that its use involves notions that need to be distinguished. We introduce four distinct kinds of SMCs, which we define operationally. These are the notions of sensorimotor environment (open-loop motor-induced sensory variations), sensorimotor habitat (closed-loop sensorimotor trajectories), sensorimotor coordination (reliable sensorimotor patterns playing a functional role), and sensorimotor strategy (normative organization of sensorimotor coordinations). We make use of a minimal dynamical model of visually guided categorization to test the explanatory value of the different kinds of SMCs. Finally, we discuss the impact of our definitions on the conceptual development and empirical as well as model-based testing of the claims of the sensorimotor approach.

Key words: embodied cognition, sensorimotor contingencies, dynamical systems, sensorimotor approach to perception, minimal cognition

This article focuses on an artificial life approach to some important problems in machine learning such as statistical discrimination, curve approximation, and pattern recognition. We describe a family of models, collectively referred to as semi-algebraic networks (SAN). These models are strongly inspired by two complementary lines of thought: the biological concept of autopoiesis and morphodynamical notions in mathematics. Mathematically defined as semi-algebraic sets, SANs involve geometric components that are submitted to two coupled processes: (a) the adjustment of the components (under the action of the learning examples), and (b) the regeneration of new components. Several examples of SANs are described, using different types of components. The geometric nature of SANs gives new possibilities for solving the bias/variance dilemma in discrimination or curve approximation problems. The question of building multilevel semi-algebraic networks is also addressed, as they are related to cognitive problems such as memory and morphological categorization. We describe an example of such multilevel models.

Constructivist philosophy and Hasok Chang’s active scientific realism are used to argue that the idea of “truth” in cluster analysis depends on the context and the clustering aims. Different characteristics of clusterings are required in different situations. Researchers should be explicit about on what requirements and what idea of “true clusters” their research is based, because clustering becomes scientific not through uniqueness but through transparent and open communication. The idea of “natural kinds” is a human construct, but it highlights the human experience that the reality outside the observer’s control seems to make certain distinctions between categories inevitable. Various desirable characteristics of clusterings and various approaches to define a context-dependent truth are listed, and I discuss what impact these ideas can have on the comparison of clustering methods, and the choice of a clustering methods and related decisions in practice.

Key words: constructivism, active scientific realism, natural kinds, categorization, mixture models, variable selection.

A goal of perception is to estimate true properties of the world. A goal of categorization is to classify its structure. Aeons of evolution have shaped our senses to this end. These three assumptions motivate much work on human perception. I here argue, on evolutionary grounds, that all three are false. Instead, our perceptions constitute a species-specific user interface that guides behavior in a niche. Just as the icons of a PC’s interface hide the complexity of the computer, so our perceptions usefully hide the complexity of the world, and guide adaptive behavior. This interface theory of perception offers a framework, motivated by evolution, to guide research in object categorization. This framework informs a new class of evolutionary games, called interface games, in which pithy perceptions often drive true perceptions to extinction.

We propose that selection favors nonveridical perceptions that are tuned to fitness. Current textbooks assert, to the contrary, that perception is useful because, in the normal case, it is veridical. Intuition, both lay and expert, clearly sides with the textbooks. We thus expected that some commentators would reject our proposal and provide counterarguments that could stimulate a productive debate. We are pleased that several commentators did indeed rise to the occasion and have argued against our proposal. We are also pleased that several others found our proposal worth exploring and have offered ways to test it, develop it, and link it more deeply to the history of ideas in the science and philosophy of perception. To both groups of commentators: thank you. Point and counterpoint, backed by data and theory, is the essence of science. We hope that the exchange recorded here will advance the scientific understanding of perception and its evolution. In what follows, we respond to the commentaries in alphabetical order.

Key words: bayesian inference, categorization, parameter estimation, perceptual categorization and identification, visual perception.

Perception is a product of evolution. Our perceptual systems, like our limbs and livers, have been shaped by natural selection. The effects of selection on perception can be studied using evolutionary games and genetic algorithms. To this end, we define and classify perceptual strategies and allow them to compete in evolutionary games in a variety of worlds with a variety of fitness functions. We find that veridical perceptions – strategies tuned to the true structure of the world – are routinely dominated by nonveridical strategies tuned to fitness. Veridical perceptions escape extinction only if fitness varies monotonically with truth. Thus, a perceptual strategy favored by selection is best thought of not as a window on truth but as akin to a windows interface of a PC. Just as the color and shape of an icon for a text file do not entail that the text file itself has a color or shape, so also our perceptions of space-time and objects do not entail (by the Invention of Space-Time Theorem) that objective reality has the structure of space-time and objects. An interface serves to guide useful actions, not to resemble truth. Indeed, an interface hides the truth; for someone editing a paper or photo, seeing transistors and firmware is an irrelevant hindrance. For the perceptions of H. sapiens, space-time is the desktop and physical objects are the icons. Our perceptions of space-time and objects have been shaped by natural selection to hide the truth and guide adaptive behaviors. Perception is an adaptive interface.

Key words: bayesian inference and parameter estimation, perceptual learning, perceptual categorization and identification, spatial cognition, evolution.

Open peer commentary on the article “An Analysis Procedure for the Micro-Phenomenological Interview” by Camila Valenzuela-Moguillansky & Alejandra Vásquez-Rosati. Abstract: The authors describe how the structures of experience unfold in the course of micro-phenomenological analysis step by step by suggesting iterative interrogation. The proposed abstraction operations ultimately deserve more thorough discussion concerning the categorization process, specifically as to the potential necessity of integrating more hierarchical steps.

Excerpt: Viewing grammar as a cognitive-semiotic mechanism grounded in perception, rather than a set of rules that govern the use of linguistic structures in writing, allows us − not only to better understand the mechanism itself, providing much more coherent explanations of grammatical categories as metasigns − but also to see analogies, unnoticed heretofore, between different languages. Guided by an understanding that language is an evolutionary extension of the human sensorium, linguistic research may become much more insightful by utilizing the cognitivesemiotic distinction “observed vs. known” in probing into the depths of natural language grammar. In particular, this categorization principle may serve as a lodestone in the studies of verbal aspect and related phenomena in different languages, freeing these studies from ungrounded speculations and helping linguists see the well-established grammatical “facts” in a new light. Most importantly, the approach to grammar outlined in this chapter may provide an empirically solid foundation for developing effective didactic techniques that would facilitate second and foreign language acquisition