Joao Kogler

Joao Kogler Jr. & Paulo Santos discuss, in chapter eleven, the geometrical and logical aspects of a cognitive agent, which distinguishes it from merely reactive and perceptive agents. What singles out the cognitive agent is the use of context- invariant information that breeds knowledge. In their approach, the perceptual system is formed by a chain of processes dealing with contextual information, beginning at the sensorial system and ending at the motor system. The perceptual chain is constrained not only at both extremities, but its transformations are geometrically connected with “holonomic” constraint propagation. On the other hand, the cognitive system comprises self-constrained processes that operate with learned transformations, so that the geometry of cognition is “non- holonomic”. Shifting to the logical approach to the problem, “qualitative spatial reasoning” is unveiled in terms of “regional connection calculus”, which describes how spatial regions are connected. The approach, as pointed by the authors, has not fared well with experimental data from cognitive psychology, which is expected since the formal approach is an abstraction from perception. Building on suggestions from advantaged properties of representations, a formalism is proposed which represents qualitative location by partitioning the visual scene around an agent into sectors, and providing relations among them, so that they form a language capable of expressing the spatial organization of the scene.

O presente capítulo examina aspectos do debate entre as concepções de percepção visual defendidas por David Marr e James Gibson, focalizando na questão das representações perceptuais versus percepção direta, conduzindo às questões mais amplas que contrastam a cognição ecológica e o computacionalismo. Esta obra reúne textos de pesquisadores de universidades brasileiras e estrangeiras que exploram as relações entre cognição, emoção e ação. Os autores se propõem a contribuir para a reflexão e o desenvolvimento de estudos que compreendam o papel e a articulação das dimensões cognitiva, afetiva e comportamental dos agentes. Apresentados no IX Encontro Brasileiro-Internacional de Ciência Cognitiva, realizado em dezembro de 2012, no campus da Unesp de Bauru, os trabalhos aqui coligidos são motivados pelos resultados das pesquisas recentes na área que têm contribuído para a compreensão tanto dos processos cognitivos, quanto da relação entre cognição e ação.

This paper proposes some working definitions of cognitive processes and related concepts, following an information-theoretical approach, and aimed at the specification of cognitive systems design. Their extension to biologically inspired cognitive applications (BICA) is also considered, verifying if their interpretation conform with the corresponding sense usually found in biology and neuroscience. We address this discussion motivated by the increasing use of the terms ‘cognition’ and ‘cognitive’ by design teams of companies, in the specification and dissemination of several new technological applications, made without providing a clear indication of their meaning and the role they play in meeting the application’s functional requirements. This situation is partly due to the imprecise presentations of these concepts available in the literature, generally not easily translatable into design requirements specification. The price paid for this deficiency increases considerably in cases of critical dependency, suggesting the need for more accurate terminology, at least for design purposes.

This brief essay discusses whether machines can be considered as artists accordingto the same standards required of human beings. It starts with considerationsregarding the nature of art, whether it can be created artificially and whatrequirements must be met for a work to be considered a work of art. Considering theaspect of art being the result of a creative conception, the question of the autonomyrequired for the authorship of artistic production is also discussed. Theconsiderations are made in the light of Peirce's semiotics and some current examplesare presented as an illustration of the state of the art. Cases of implementations viadeep learning based on generative adversarial networks – GAN – are analysed, and some considerations are made regarding the potentialities and advantages of using methods based on active inference.

Abstract: This chapter aims to present the elements of Shannon’s Information Theory in an accessible way, situate it historically, discuss its main implications and aspects of its use and applicability, comment on common mistakes of its incorrect use, and indicate its extensions. The heuristic approach here adopted through a simplified perspective, however, does not compromise the precision and accuracy of the analyses of the fundamental aspects essential for understanding Shannon’s legacy and the way he influenced science and revolutionised technology. Whenever interesting, historical aspects will be included to help understand the development of ideas and concepts.

The aim of this paper is to provide an account of extension that strictly follows from the organizational theory of autonomous systems, further developing recent enactive accounts of extension and incorporation. We examine Moreno and Mossio’s definition of an autonomous system, developed in Biological Autonomy. Then, we argue that their definition provides two different ways an autonomous system can extend its autonomy to external entities (extension by constraint surrogate and extension by constraint composition), together with a criterion for each case of extension. We also consider that each case can be characterized by transformations of the autonomous system’s viability space, normative field and topological unity. We discuss the consequences of our account for the recent enactive views on incorporation and extension, arguing that the notion of ‘extension’ does not necessarily require functionalism and that it can be usefully adopted by enactivism. Finally, we show that a productive tension is created between the extension cases developed here and the enactive accounts of incorporation.

This issue of COGNITIVE SYSTEMS RESEARCH features seven articles originated from selected works submitted to EBICC 2015 – Tenth International Brazilian Meeting on Cognitive Science, and orally presented at the event, which took place in the city of São Paulo, Brazil on December 2015. These papers provide a glimpse of the wide spectrum of aspects of cognitive science, always present in the several editions of the meeting since its inception in 1995. Organized by the Brazilian Society of Cognitive Science, this interdisciplinary event brought together researchers in the fields of Cognitive Science and Philosophy of Mind. The extended and updated versions of the selected works are highlighted as follows.

In this essay we examine the relationships between Big Data and cognition, in particular human cognition. The reason for exploring such relationships lies in two aspects. First, because in the domain of cognitive science, many speculate about the benefits that the uses of Big Data analysis techniques can provide to the characterization and understanding of cognition. Secondly, because the scientific and technological sectors that promote data analysis activities, particularly statistics, computer science and data science, naturally accustomed to working with Big Data, have in recent years used the idea of ​​cognition. and its related concepts as terms that seem capable of remedying the deficiencies of the era of symbolic artificial intelligence, as a response to the automation of typically human activities in the process of analyzing data and using its results. of data science, seeking to understand what Big Data really is and to investigate whether the use of cognition models could be applied to the sector. On the other hand, we will analyze the potential of using Big Data to help cognitive science. We also tried to provide a certain didactic character in some points, aiming to help the understanding, by non-specialists, regarding some principles and aspects of the methodology of data science and statistics that will eventually be mentioned in the development of our analysis. (Translated from original)

This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role of language and communication in cognition, the nature of embodied cognition, selective topics in visual cognition, brain connectivity, computation and simulation, social and technological issues within the cognitive sciences, and significant issues in the history of neuroscience. This book will be of interest to both professional researchers and newer students and graduate students in the fields of cognitive science—including computer science, linguistics, philosophy, psychology and neuroscience. The essays are in English and are designed to be as free as possible of technical jargon and therefore accessible to young scholars and to scholars who are new to the cognitive neurosciences. In addition to several entries by single authors, the book contains several interesting roundtables where researchers contribute answers to a central question presented to those in the focus group on one of the core areas listed above. This exciting approach provides a variety of perspectives from across disciplines on topics of current concern in the cognitive sciences.

The computational theory of cognition, or computationalism, holds that cognition is a form of computation. Two issues related to this view are comprised by the goal of this paper: A) Computing systems are traditionally seen as representational systems, but functional and enactive approaches support non-representational theories; B) Recently, a sociocultural theory against computationalism was proposed with the aim of ontologically reducing computing to cognition. We defend, however, that cognition and computation are in action, thus cognition is just a form of computing and that cognition is the explanatory basis for computation. We state that: 1. Representational theories of computing recurring to intentional content run into metaphysical problems. 2. Functional non-representational theories do not incur this metaphysical problem when describing computing in terms of the abstract machine. 3. Functional theories are consistent with enactive in describing computing machines not in a strictly functional way, but especially in terms of their organization. 4. Enactive cognition is consistent with the computationalism in describing Turing machines as functionally and organizationally closed systems. 5. The cognitive explanatory basis for computing improves the computational theory of cognition. When developed in the human linguistic domain, computer science is seen as a product of human socionatural normative practices, however, cognition is just an explanatory, not ontological, basis for computing. The paper concludes by supporting that computation is in action, that cognition is just one form of computing in the world and the explanatory basis for computation.