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Overview of Contributions Overview of Contributions he first papers address the epistemological sentationalism”). Evidence for the first comes e.g. status of representation and possible catego- from connectionism which has demonstrated that T rizations. These rather general consider- brain-like structures can function without explicit ations about representation are followed by contri- representations. Arguments for the second are of a butions that focus on computational approaches, philosophic nature denying the possibility of speak- especially on how meaning can be simulated in arti- ing of fixed entities of the world, and, instead, pro- ficial devices, and how meaning can be grounded. posing that the “things” are defined only with Solutions are offered on various levels, among them respect to their user and thus cannot be “mapped” symbol grounding and system-theoretical consider- onto the brain of that user. Matthias Scheutz inves- ations to representation. Various disciplines inde- tigates the ontological status of representations, and pendently arrive at emphasizing the importance of questions whether they are entities on their own; he actions for representations and the necessity to argues that whether something counts as represen- close the sensory–motor loop; examples from the tation of something else is dependent on the level of perspective of computational approaches (“embod- description. By talking about a mental structure rep- iment” into an environment), the neuroscientific resenting something in the world, one implies that perspective (“top-down” processes), the psycholog- these two things exist on two different ontological ical perspective and others are presented. Several levels. This is not true, however, since the mind and papers address the role of social interactions—in the things of the world are both entities within our particular language—as a means of stabilizing sys- cognitive experience. Thus, the problem of repre- tems, and in the emergence of meaning. The deep sentation arises only as artifact of our describing the epistemological implications connected with the phenomenon of cognition. Daniel Hutto explores above considerations are discussed in the final the difference between non-conceptual representa- chapter of the volume dedicated to constructivist tions and conceptual representations and asks the approaches. Following the idea of a true interdisci- question whether it makes sense to define represen- plinary approach, the contributions to the various tation on the lowest level of abstraction or on the sections are organized exclusively with respect to highest level. thematic content rather than to scientific discipline. Is it possible to simulate meaning or cognition? The remainder of this overview presents the papers The issue of computation to representation is pre- and their mutual relationship in more detail. sented in the chapter “Computational Approaches”. In the first chapter, dedicated to theoretical con- The paper by Georg Schwarz draws conclusions siderations, Georg Dorffner provides an introduc- for the functioning of the brain from a computa- tion to the problem of representation by defining tional perspective. From a philosophical point of three types of representation. He shows that connec- view, William Robinson tries to address a contro- tionism solves several problems of representation versy in computational approaches to cognition by and actually helps to abandon one of these types of introducing a distinction between cognition and representation. Similarily, Alfredo Pereira investi- cognitive abilities. Robert French makes the argu- gates two types of the representations used in the ment that creating representations cannot be sepa- neurosciences, perceptual and executive processes. rated from manipulating them. Moreover, he Anthony Chemero tries to classify possible cri- emphasizes the context-dependency of linguistic tiques regarding representations. He presents two terms (one of the reasons that computational lin- types of anti-representationalism: either the repre- guistics is non-trivial matter) and, as a consequence, senting structure can be questioned (“empirical the distractive character of context-laden represen- anti-representationalism”), or the represented struc- tations. Andrew Coward proposes that natural ture can be questioned (“metaphysical anti-repre- pressures have resulted in biological brains having Understanding Representation in the Cognitive Sciences Edited by A. Riegler, M. Peschl, and A.von Stein. Kluwer Academic/Plenum Publishers, New York, 1999 19 20 Understanding Representation in the Cognitive Sciences simple functional architectures. The type of archi- large scale cortical interactions, he derives a tecture constrains the type of representations which dynamical view of cortical representation based on are possible. interareal pattern constraints and large-scale relax- While connectionism overcame some of the prob- ation. lems derived from considering the brain as a von In a related realm, away from representations Neuman Computer, serious new questions came understood as projections of environmental entities into focus. With simulating representations in neu- onto mental structures, several disciplines indepen- ronal networks it became even more obvious that dently discovered the importance of actions for rep- the problem to be solved was that the meaning was resentations. They propose to close the sensory– put into the system by the engineer. Whether the motor loop. (For this topic of parallelisms in scien- state of the network would stand for something is tific/philosophical developments: see the comment defined by an external observer but is not inherent by Wolf Singer in the discussions, page 293). In to the system. This problem of the foundation of modeling, the grounding problem described above meaning is referred to as the grounding problem, introduced the relevance of interaction for represen- which is treated in the chapter on “Symbol Ground- tations; embodied systems that interact with their ing and Language”. Tom Ziemke provides a review environment in a sensory–motor loop are created. about the grounding problem and it’s two proposed Philosophically, constructivism and the theory of solutions. The first solution of grounding is ground- autopoietic systems demonstrated that what we per- ing a symbol to an input, which was first proposed ceive as representations of a predefined external by Stevan Harnad. The papers by Nathan Chan- world is better described as constructions that serve dler et al. and Christian Balkenius & Simon Win- to successfully generate behavior. In neuroscience, ter present such models on grounded language sys- the old concept that environmental objects are tems. As described in the paper by Ziemke, this, mapped onto neurons in a feed-forward manner is however, is only a partial solution; the real break- challenged by anatomical and physiological evi- through is only obtained when a robot is really dence. It has been shown that information does not embedded into an environment and interacting with exclusively flow from the sensors to the higher brain it. Examples of this kind of grounding are given by areas, where the representations are then thought to Mark Wexler and Ralf Möller (see below). be used for “thinking” and the final activation of Not only in classical AI but also in connection- motor programs (“bottom up”). Rather, massive ism, meaning and representations are mostly of a activity is transported the other way around (“top- static nature. Thus, although distributed, representa- down”). Thus motor activity, i.e., planned actions, tions are still very much treated like “boxes”. Cog- can be viewed as supervising the incoming signals nition, however, is dynamic and it needs time (see and thus structuring cortical representations them- also discussion, page 290). Systems theory provides selves. Psychophysical evidence, such as the fig- a framework that encompasses these issues (chapter ure–vase ambiguity, show that perception is ambig- “Cognition as a Dynamical System”). From a psy- uous, dependent on priming and expectancy. Thus, chological point of view, Pim Haselager provides a several approaches come to the conclusion that per- review about the relevance of dynamical systems ception is not a passive, feedforward process of theory to the topic of representation and its (philo- mapping but an active construction, where the need sophical) classification in the context of behavior- for action creates an hypothesis about the environ- ism. Marius Usher & Ernst Niebur present neuro- ment which is then compared to the incoming sen- scientific evidence and a model demonstrating that sory signals. The chapter “Relevance of Action for neural representations are active processes which Representation” is dedicated to these problems. can mediate contextual computation and bind rela- The idea of “the inversion of sensory processing tional properties. Ken Mogi discusses the concept by feedback pathways” was introduced by Erich of time and causality in the relation of perception Harth. In his paper, he describes neurophysiologi- and neural firing. His principle of interaction simul- cal evidence for a scenario where processing is not taneity provides an explanation for the origin of from the periphery to the higher brain areas but subjective time. Steve Bressler presents a complex- rather the other way around. He presents a model systems theory approach to representation and cog- where a cortical hypothesis (“internal sketchpad”) nition. Inspired by empirical
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