Markus F. Peschl

Understanding representation in the cognitive sciences

This paper discusses the notion of representation and outlines the ideas and questions which led to the organization of this volume. We argue for a distinction between the classical view of referential representation, and the alternative concept of system-relative representation. The latter refers to situated cognitive processes whose dynamics are merely modulated by their environment rather than being instructed and determined by it.

Does Representation Need Reality

This paper discusses the notion of representation and outlines the ideas and questions which led to the organization of this volume. We argue for a distinction between the classical view of referential representation, and the alternative concept of system-relative representation. The latter refers to situated cognitive processes whose dynamics are merely modulated by their environment rather than being instructed and determined by it.

Designing and Enabling Spaces for collaborative knowledge creation and innovation

knowledge creation and innovation. We refer to these artifacts as Enabling Spaces, and they comprise architectural, technological (ICT), social, cognitive, organizational, cultural, as well as emotional dimensions. The paper claims that innovation is a highly challenging social and epistemological process which needs to be facilitated and enabled through supporting (infra-)structures. Our starting point is that innovation can no longer be understood as a mechanistic knowledge creation process. The process of enabling is introduced as an alternative to such traditional approaches of innovation. Enabling is the main design principle that underpins Enabling Spaces and ICT plays an important role in it. These concepts will be illustrated by a case study and concrete examples. The paper culminates in the derivation of a set of design principles, ICT based and otherwise, for Enabling Spaces.

Representation still matters: Cognitive engineering and user interface design

With the increased utilization of cognitive models for designing user interfaces several disciplines started to contribute to acquiring and representing knowledge about users, artifacts, and tasks. Although a wealth of studies already exists on modeling mental processes, and although the goals of cognitive engineering have become quite clear over the last decade, essential epistemological and methodological issues in the context of developing user interfaces have remained untouched. However, recent challenging tasks, namely designing information spaces for distributed user communities, have led to a revival of well known problems concerning the representation of knowledge and related issues, such as abstraction, navigation through information spaces, and visualization of abstract knowledge. All of these issues are associated with mental processes and thus, might become part of cognitive models. In this paper we reveal epistemological and methodological assumptions in the field of cognitive modeling as wel...

The Representational Relation Between Environmental Structures and Neural Systems: Autonomy and Environmental Dependency in Neural Knowledge Representation

In this paper it will be shown that in neural systems with a recurrent architecture, the traditional concepts of knowledge representation cannot be applied any more; no stable representational relationship of reference can be found. That is why a redefinition of the relationship between the states of the environment and the internal representational states is proposed. Studying the dynamics of recurrent neural systems reveals that the goal of representation is no longer to map the environment as accurately as possible to the representation system (e.g., to symbols). It is suggested that it is more appropriate to look at neural systems as physical dynamical devices embodying the (transformation) knowledge for sensorimotor integration and for generating adequate behavior enabling the organisms survival. As an implication the representation is determined not only by the environment, but highly depends on the organization, structure, and constraints of the representation system as well as the sensory/motor systems which are embedded in a particular body structure. This leads to a system relative concept of representation. By transforming recurrent neural networks into the domain of finite automata, the dynamics as well as the epistemological implications become more clear. In recurrent neural systems a type of balance between the autonomy of the representation and the environmental dependence/influence emerges. This not only affects the traditional concept of knowledge representation, but has also implications for the understanding of semantics, language, communication, and even science.

From mechanisms to function: an integrated framework of animal innovation

Animal innovations range from the discovery of novel food types to the invention of completely novel behaviours. Innovations can give access to new opportunities, and thus enable innovating agents to invade and create novel niches. This in turn can pave the way for morphological adaptation and adaptive radiation. The mechanisms that make innovations possible are probably as diverse as the innovations themselves. So too are their evolutionary consequences. Perhaps because of this diversity, we lack a unifying framework that links mechanism to function. We propose a framework for animal innovation that describes the interactions between mechanism, fitness benefit and evolutionary significance, and which suggests an expanded range of experimental approaches. In doing so, we split innovation into factors (components and phases) that can be manipulated systematically, and which can be investigated both experimentally and with correlational studies. We apply this framework to a selection of cases, showing how it helps us ask more precise questions and design more revealing experiments.

Autonomy: starting point and goal of personal and social change

Purpose – Empowerment describes the processes of how to gain and increase autonomy and self‐determination in ones own environment. Typical examples for empowerment processes can be found in: citizens initiatives, human rights movements, and other social movements or self help groups. This paper shows that empowerment processes have to be understood as “knowledge processes”. A link between empowerment and the methods of knowledge management will be established. It is inspired by Heinz von Foersters ideas of self‐regulated processes in nervous systems.Design/methodology/approach – In a first step the concept of empowerment will be presented. Secondly, it will be shown which role knowledge is playing in this context. In the last part practical implications of these considerations will be discussed.Findings – The motivation for engaging in civil society issues is heavily dependent on personal knowledge and on the abilities to access knowledge resources. A constructivist paradigm turns out to be fertile. Dis...

CONSTRUCTIVISM, COGNITION, AND SCIENCE - AN INVESTIGATION OF ITS LINKS AND POSSIBLE SHORTCOMINGS

This paper addresses the questions concerningthe relationship between scientific andcognitive processes. The fact that both,science and cognition, aim at acquiring somekind of knowledge or representationabout the “world” is the key for establishing alink between these two domains. It turns outthat the constructivist frameworkrepresents an adequate epistemologicalfoundation for this undertaking, as its focusof interest is on the (constructive)relationship between the world and itsrepresentation. More specifically, it will beshown how cognitive processes and their primaryconcern to construct a representation of theenvironment and to generate functionallyfitting behavior can act as the basis forembedding the activities and dynamics of theprocess of science in them by making use ofconstructivist concepts, such as functionalfitness, structure determinedness, etc.Cognitive science and artificiallife provide the conceptual framework of representational spaces and their interactionbetween each other and with the environmentenabling us to establish this link betweencognitive processes and thedevelopment/dynamics of scientific theories.The concepts of activation, synaptic weight,and genetic (representational) spaces arepowerful tools which can be used as“explanatory vehicles”for a cognitivefoundation of science, more specifically forthe “context of discovery” (i.e., thedevelopment, construction, and dynamics ofscientific theories and paradigms).Representational spaces do not only offer us abetter understanding of embedding science incognition, but also show, how theconstructivist framework, both, can act as anadequate epistemological foundation for theseprocesses and can be instantiated by theserepresentational concepts from cognitivescience. The final part of this paper addresses somemore fundamental questions concerning thepositivistic and constructivist understandingof science and human cognition. Among otherthings it is asked, whether a purelyfunctionalist and quantitative view of theworld aiming almost exclusively at itsprediction and control is really satisfying forour intellect (having the goal of achieving aprofound understanding of reality).

The Role of Cognitive Modeling for User Interface Design Representations: An Epistemological Analysis of Knowledge Engineering in the Context of Human-Computer Interaction

In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer.We show that in a first step it is necessary to study and investigate the different levels and forms of representation that are involved in the interaction processes between computers and human cognitive systems. Only if designers have achieved some understanding about these representational mechanisms, user interfaces enabling individual experiences and skill development can be designed. In this paper we review mechanisms and processes for knowledge representation on a conceptual, epistemological, and methodologieal level, and sketch some ways out of the identified dilemmas for cognitive modeling in the domain of human-computer interaction.

Why space matters for collaborative innovation networks: on designing enabling spaces for collaborative knowledge creation

As opposed to managing or controlling innovation processes, this paper proposes the notion of enabling as a more suitable approach to innovation. As a consequence, the concept of Enabling Spaces is introduced as a space that is designed in such a way that it enables and facilitates processes of collaborative knowledge creation and innovation. In that context a rather broad notion of space is applied: It goes far beyond architectural/physical space by integrating social, cognitive, emotional, organizational, and epistemological dimensions in an interdisciplinary manner. Both the theoretical background and the methodological approach and design process will be presented. Furthermore, we will discuss a case for an Enabling Space which functions as a collaborative innovation network. It will turn out that Enabling Spaces and Collaborative Innovation Networks (COINs) share a lot of characteristics, attitudes, and values.