NTCS'97

Abstracts

Last update: April 29, 1997


Annika Wallin Is there a way for constructivism to distinguish what we experience from what we represent?

When constructivism gives up reality as a way of accounting for representations it looses a powerful tool of explanation. Why do we have the representations we have? How are they interrelated? This article attempts to investigate what possible means a constructivistic theory has to maintain the distinction between representations and experience, between memory and imagination, and between correct and mistaken perceptions. Phenomenological qualities and coherence are the solutions advocated, but how they are combined will have an impact on what sort of constructivistic theories that can be maintained.


Marius Usher and Ernst Niebur Active neural representations: Neurophysiological data and conceptual implications

We discuss the nature of cognitive representations and present a scheme for the encoding of information which accounts for both categorical and graded aspects of cognitive events. Accordingly, object categories are mapped onto the identity of cell populations via the process of categorical perception, while graded aspects such as vividness and confidence level are mapped onto the rate and degree of synchrony of neural populations. We show that the process of categorical perception can solve the problem of reference of perceptual-cognitive states, and we demonstrate by computer simulation models that synchrony can encode for grouping and binding of coherent information. In these models, recurrent connections play a major role in generating synchronised activity in cell populations which receive consistent sensory stimulation, and in generating temporal fluctuations in their discharge rate. We suggest that such fluctuations underlie autonomous computations reflecting fluctuations in the certainty (confidence level) of perceptual and cognitive hypothesis.


Steven L. Bressler The Dynamic Manifestation of Cognitive Structures in the Cerebral Cortex

Cognitive structures are organized systems of information that embody the knowledge used to construct an individual's reality. Having phylogenetic and ontogenetic determinants, they reside latently in the connectional organization of the cerebral cortex, both within and between areas. Different cortical areas, containing separate categories of knowledge in their local associative memories, operate in conjunction with one another to instantiate cognitive structures in perceptuo-motor behavior. As multiple areas recursively interact in large-scale networks, their mutual constraint leads to the emergence of coherent large-scale activity patterns. These patterns constitute a consistent construction of reality that fits the constraints imposed by the structures of the internal and external environments. This construction is the dynamic manifestation of cognitive structures in the cerebral cortex.


Anthony Chemero Two types of anti-representationism: A taxonomy

Anti-representationism is in the air. In the last few years, many philosophers and cognitive scientists have considered or even embraced the claim that cognition is not representational, often without giving explicit consideration to what exactly this means. The point of this essay is to try to make some sense of claims that cognitive science can do without representations by proposing a taxonomy for them. In what follows, I will make a distinction between two different varieties of anti-representationism. And, with this distinction in hand, I will consider some actual scientific work that has led to claims that cognitive science can do, at least in part, without representations.


Horst Hendriks-Jansen Does Natural Cognition Need Internal Knowledge Structures?

This paper argues that situated robotics and dynamical systems theory can provide conceptual and empirical tools to support a view of cognition as the interactively emergent capacity to act appropriately in specific situations. It claims that such an explanation accords more readily with evolutionary and developmental accounts than does the traditional framework of cognitive science, and that it is more likely to lead to an understanding of the mechanisms that subtend cognition.


Matthias Scheutz The Ontological Status of Representations

The goal of this paper is to argue that the ontological status of representations can only be evaluated within a theory. In other words, what counts as representation, or whether a certain representation is better than another one, depends solely on the (level of) description of the phenomenon under scrutiny. It is shown how "representation", being a semantic notion, can be defined in terms of the notion "meaning". For cognitive science, in particular, it follows that representations, functioning as mere descriptive devices to facilitate one's goal of explaining and modeling brain/thought processes, cannot in and by themselves give rise to ontological or epistemological claims.


Michael Pauen Reality and Representation. Qualia, Computers, and the "Explanatory Gap"

Three problems concerning the mutual relation of reality and representation are discussed. Although there is no direct access to reality, a structural similarity between reality and representation can be assumed. A holistic account of qualia can help to explain how this structural similarity is achieved. On this account, qualia have a relational, not an intrinsic status. Finally, the 'explanatory gap argument' which seems to challenge this account is rejected because it confuses the first and third person perspective on the mind/brain. While corresponding with the PDP-approach in AI, the results contradict the traditional brain/computer analogy. All in all, these considerations may help to dissolve some of the philosophical puzzles around the mind/brain relationship and demonstrate that the relevant questions can be solved by empirical research.


Georg Schwarz Can Representation Get Reality?

The title of this conference‹Does Representation Need Reality"‹suggests that it is at least possible for a system to represent its environment. The aim of this paper is to argue that there exists an important class of representations‹those employed by computing systems‹where this assumption may not be warranted.


William S. Robinson Representation and Cognitive Explanation

Representations, it is argued, cannot have effects as representations; yet, even so, they are essential to some explanations in cognitive science. These apparently incompatible claims can be reconciled if we distinguish between explaining cognitive abilities and explaining cognition. Certain cognitive abilities can be seen to require representations for their explanation; but explanations of this type cannot explain how the required representations come to be available, or come to be appropriately connected. A clear understanding of the distinction between explaining cognitive abilities and explaining cognition suggests a certain approach to the latter project, and throws light on some recent controversies.


Pim Haselager Is Cognitive Science Advancing Towards Behaviorism?

Proponents of the Dynamical Systems Theory (DST) have dismissed the connectionist reaction against classical cognitive science as not going far enough. This paper addresses the question of where cognitive science is supposed to be going. It is argued that there is a growing tendency within cognitive science to replace structure-sensitive processes of a computational nature by associative processes of a neurophysiological kind. DST offers a conceptual repertoire that goes beyond traditional connectionism in its even greater emphasis on time and change at the expense of the notions of computation and representation. More specifically, it is suggested that Edelman's neurodynamical work on conceptual categorization can be located within an associationistic and early behavioristic tradition with its attempt to explain behavior on the basis of associative processes in the brain. Although this is a tradition not currently favoured by cognitive science, a recognition of DST's associationistic tendency and its similarities with early behaviorism seems called for and, moreover, does not necessarily imply a weakening of its relevance for the study of cognition.


Tom Ziemke Rethinking Grounding

The 'grounding problem' poses the question of how the function and internal mechanisms of a machine, natural or artificial, can be intrinsic to the machine itself, i.e. independent of an external designer or observer. Searle's and Harnad's analyses of the grounding problem are briefly reviewed as well as different approaches to solving it, based on the cognitivist and the enactive paradigms in cognitive science. It is argued that, although the two categories of grounding approaches differ in their nature and the problems they have to face, both, so far, fail to provide fully grounded systems for similar reasons: Only isolated parts of systems are grounded, whereas other, essential, parts are left ungrounded. Hence, it is further argued that grounding should instead be understood and approached as radical bottom-up development of complete robotic agents in interaction with their environment.


Christian Balkenius and Simon Winter Explorations in Synthetic Pragmatics

We explore a number of pragmatic principles of communication in a series of computer simulations. These principles characterize both the environment and the behavior of the interacting agents. We investigate how a common language can emerge, and when it will be useful to communicate rather than to try the task without communication. When we include the cost of communicating, it becomes favorable to communicate only when expectations are not met.


N. Chandler, V. Balendran, L. Evett, and K. Sivayoganathan On the Importance of Reality in Representations

Symbol grounding has been put forward as a candidate solution to the problem of associating intrinsic meaning obtained from sensorimotor data, to the arbitrary symbols that are so common in the cognitive domain. This paper focuses on the notion of how intrinsic meaning may be acquired and represented within an artificial cognitive system and considers how this task is influenced by varying the initial representations of sensory data and also the internal mechanics of the learning mechanism employed.


Peter Gärdenfors Does Semantics Need Reality?

The article focuses on four questions for a theory of semantics: the ontological, semantic, learnability and communicative questions. It is shown how different realist, cognitivist and constructivist semantic theories answer the questions.


Chris Browne and Shan Parfitt Iconic Learning and Epistemology

This paper describes a neural network approach to building a system which is able to learn higher-level concepts from low-level sensory-motor interactions with environment. Such a system would provide a model for Karmiloff-Smith's proposed process of representational redescription (Karmiloff-Smith 1995) as well as satisfying, to a large extent, Fodor and Pylyshyn's criteria for a cognitive architecture (Fodor and Pylyshyn 1988). Since the particular system described in this paper is recursive the approach is likely to provide some insight into the origins of the human high-level representational system.


Mark Claessen RabbitWorld: The Concept of Space Can Be Learned

This article presents a learning model that is able to form a concept of space through interaction with its environment. This model takes the form of a neural network that has to predict the movement of a population of rabbits on a virtual world. The movement of the rabbits accords to a biological population model. Encoded in the weighted connections of the trained network is a concept of space, even though the network was never given any direct information about movement or direction.


Valentin D. Constantinescu Recognition as Interaction between Perception and Expectancy

In a previous paper I presented experimental EEG evidence showing that in subjects with normal cognitive functions, the visual evoked responses present a variability pattern (VP) related to the stimulation event and not to some random background activity of the brain. The absence of the VP strongly correlates with the absence of cognitive function in patients. Two of my conclusions were (a) that VP reflects the cognition function as distinct from the phenomenal perception in the visual process and (b) that the neuronal cognitive activity has a chaotic component, responsible for the VP. In the present paper I present a model of the recognition process, explaining among others why the above-mentioned neuronal activity would be chaotic and how the neuronal populations involved in "high-level vision" (i.e. at the transition from perception to cognition) would interact in order to perform the process of recognition. The interaction is represented here as a chained activation of the neuronal populations, driven recurrently by the exogenous perception of visual attributes and the endogenous expectancy. The chaotic component of the visual responses can be sufficiently explained by a variable, unpredictable sequence of attribute processing.


L. Andrew Coward Unguided Categorization, Direct and Symbolic Representation,

Severe constraints apply to the architecture of any system which uses large numbers of components to deliver complex functionality. If not taken into account, these constraints can invalidate conclusions drawn from simulation of cognitive subsystems. The pattern extraction hierarchy is a connectionist architecture which can satisfy these constraints. Within the architecture, functionality is partitioned at a high level in a manner which is consistent with the range of qualitative functionality available from neurons. A system with this architecture can perform unguided categorization resulting in internal representations experienced as mental images. These internal representations function to generate alternative behaviors and select the most appropriate. Functional descriptions of cognition can therefore be created which make use of grounded representations supported within a connectionist architecture. A scenario for the step by step development of human cognition is proposed on the basis that biological brains have the pattern extraction hierarchy architecture. This scenario demonstrates how the ability to generate behaviors appropriate for very complex situations uses a constant succession of mental images and has developed through the interaction of verbal and tool making skills.


Karl C. Diller Representation and Reality: Where Are the Rules of Grammar?

By viewing language as a 'complex adaptive system,' and particularly as a form of 'artificial life' (as opposed to a static system of generative rules), we raise new issues with regard to representation and reality in language. In the generative framework of Chomsky, "languages" such as German or English (called 'e-languages' or "externalized languages") were regarded as having no reality and having no import for linguistic theory; language was an individual phenomenon in the mind/brain of an individual. In the connectionist framework, one gets what appears to be rule-governed behavior from systems that do not have the rules explicitly coded within them; if rules of grammar have any reality as rules, they would have to be in the external languages. With 'artificial life,' we have a framework for seeing languages as variable and complex adaptive systems with a certain reality ("patterns in space/time") and with "lives of their own" even though these languages are dependent on human agents. The argument has four parts: 1. The Question; 2. Background; 3. Making sense of E-languages as complex adaptive systems: Representation needs Reality; 4. Language as Artificial Life: Reality needs Representation; and 5. Does Representation Need Reality? In terms of the question of this workshop, "Does representation need reality?", when we see language as artificial life we find a complex relationship between reality and representation. In complex adaptive systems, in systems of artificial life, and more specifically in shared linguistic systems (as opposed to individual systems of cognition), Representation needs Reality, and Reality needs Representation.


J. Richard Eiser Representation and social reality: Can cognitive science be socialized?

Several areas of research within social psychology depend on assumptions about underlying cognitive processes. These assumptions have not typically been examined from the perspective of cognitive science. This paper will focus on two theoretical constructs, the self and attitudes. In constrast to more traditional models of symbolic representation and rationalistic decision-making, a cognitive science perspective allows these to be viewed as habits or patterns of thought and behaviour that depend on learnt associations between multiple features of people's experience. The observation that individuals can display different characteristics and attitudes in different stituations suggests the importance of context-dependent learning, resulting in multiple attractors. It is suggested that the notions of parallel constraint satisfaction and unsupervised learning may be helpful for the understanding of such processes.


Robert M. French When Coffee Cups Are Like Old Elephants or Why Representation Modules Don't Make Sense

I argue against a widespread assumption of many current models of cognition ­ namely, that the process of creating representations of reality can be separated from the process of manipulating these representations. I hope to show that any attempt to isolate these two processes will inevitably lead to programs that are either basically guaranteed to succeed ahead of time due to the (usually carefully hand-crafted) representations given to the program or that that would experience combinatorial explosion if they were scaled up. I suggest that the way out of this dilemma is a process of incremental representational refinement achieved by means of a continual interaction between the representation of the situation at hand and the processing that will make use of that representation.


Daniel D. Hutto Cognition without Representation?

In addressing the question "Do representations need reality?", this paper attempts to show that a principled understanding of representations requires that they have objective, systematic content. It is claimed that there is an interesting form of non-conceptual, intentional content which is processed by non-systematic connectionist networks and has its correctness conditions provided by a minimalist teleosemantics; but this type of content is not properly representational. Finally, I consider the consequences that such a verdict has on eliminativist views that look to connectionism as a means of radically re-conceiving our understanding of cognition.


Amy Ione Symbolic Creation and Re-presentations of Reality

This paper postulates that representation is a necessary component of any inquiry into cognition and that it is through the construction and re-presentation of ideas that we most effectively bring culture, communication, and consciousness into cognitive investigations. I am calling this process symbolic creation and defining it as a combination of cognitive self-regulation and emergent consciousness. The historical relationship between art and science is used to illustrate how symbolic creation works and a discussion of computer innovations and information processing capabilities serves as a counterpoint to the historical examples. I conclude that when symbolic creation is a part of the activity of model-making we re-present ideas in forms that foster human communication and, in turn, benefit our studies of cognition, consciousness, life, and the ever-changing relationship between organisms and the environment.


Ken Mogi Response Selectivity, Neuron Doctrine, and Mach's Principle in Perception

I discuss the principle that bridges neural firing and perception. I start from the assumption that in order to understand perception, the state of neural firing in the brain is necessary and sufficient (the neuron doctrine in perception). I argue that the concept of response selectivity, currently the de facto central dogma in explaining the relation between neural firing and the brain, is incompatible with the neuron doctrine. I suggest that we start instead from Mach's principle as applied to the neural correlates of perception. I propose to define a percept as an interaction-connected firings of neurons, not as a single (or an ensemble of) neuron(s) which selectively respond(s) to a particular set of stimulus, as is assumed under the paradigm of response selectivity. This definition of percept by necessity leads to an interesting argument about the neural basis of psychological time, namely the principle of interaction simultaneity. Finally, I discuss the relevance of the twistor formalism to the foundations of neuropsychology.


Ralf Möller Perception through Anticipation. An Approach to Behaviour-based Perception

The 'information processing metaphor' as the traditional approach to visual perception suffers from a number of conceptual problems, which are due to the existence of purely sensory representations and the separation between perception and generation of behaviour. Based on this criticism and a discussion of alternative approaches, a contrary theory of perception is presented. This approach of 'perception through anticipation' tries to avoid the problems of the information processing metaphor by replacing sensory with sensorimotor representations and by considering perception as an active and generative process rather than as a pure projection. Perception of space and shape is assumed to be a process anticipating the sensory consequences of actions; appropriate actions are selected within the same process. This approach could provide a new solution to invariance and constancy problems. Starting from an abstract description of perception and action selection, two different models for this approach are presented: the first at a microscopic level modeling the architectonics of the cerebral cortex, and the latter at a macroscopic one, where the basic building blocks are associative memories.


Alfredo Pereira Junior The Concept of Representation in Cognitive Neuroscience

The following argument is presented here: 1) the term "representation" refers to a diversity of entities and processes, in the context of neuroscience; 2) the concept of representation may be understood in a stronger sense, referring to a global correspondence between structures or processes; or in a weaker sense, of a partial correspondence; 3) from the point of view of empirical sciences, brain representations constitute a partial correspondence to their respective objects.


Hanna Risku Constructivist Consequences: Translation and Reality

This paper identifies the theory of the General Communication System with its view of information as stable, storable and transferrable entities and the machine translation inspired search for the language of thought as the main trends in past cognitive scientifically relevant research in translation. The present reorientation with its remarkably different set of research questions is introduced. The contextuality of cognition, the twofold process of interpretation by meaning and sense construction and the development of cultural and expert competences are depicted as the foundation of a cognitive scientifically coherent picture on translation. Finally, it is shown how the introduction of the concept of compatibility revolutionizes the epistemological foundation of translation: the theory of linguistic reproduction is abandoned, and translation is seen as active construction of new meanings and situations.


Armagan Yavuz and David Davenport PAL: A Constructivist Model of Cognitive Activity

One way to synthesize intelligence is building an agent that can potentially learn arbitrary skills and let it learn by interacting with the environment the way human beings do. In this paper we describe our constructivist cognitive model PAL (ProcedurAlLearner) which we believe is a good starting point for this objective. PAL learns to adjust its goal-directed behavior according to causal relations in the world by trying to predict the next state of its sensors. It constructs new prediction mechanisms whenever it detects frequently repeating patterns of activity in its internal processes.


Tom Routen Habitus and animats

The assumption that adaptive behaviour research is immune from Heideggerian critiques which have seen to be relevant to traditional AI is false. Behaviour-Based ideas are in accordance with an aspect of the critique but omit the essential role of language.


Astrid von Stein Does the brain represent the world? Evidence against the mapping assumption

Whatever approach regarding internal representations, the idea was always that of a mapping of an outside world, more or less successfully performed by our cognitive apparatus. In the following we want to develop a principally different approach where representation is no more considered any kind of mapping of a predefined external reality, but simply as stabilities in the coupling between organisms and their local environment. Since this kind of representation evolves in the dynamic interaction with the environment it is a fundamentally active process of construction and not a passive mapping. Neuroscientific and psychological evidence favor this concept over old concepts on purely bottom-up mapping of the environment.

Weiss, S., Müller, H. M. & Rappelsberger, P. Processing concepts and scenarios: electrophysiological findings on language representation

Studying the underlying neurological substrate of language processing with electrophysiological techniques, we could provide evidence for a physiological reality of linguistic categories.The processing of abstract concepts (Nouns) activates different networks in different brain regions, thus showing a different representation than concrete concepts. As we have demonstrated earlier this is only true with respect to those frequencies of the EEG, which reflect higher cognitive processes. In other frequencies the processing of both abstract and concrete nouns activates similar networks.This can be explained by the fact that mere acoustical word perception does not differ between concrete and abstract nouns. The comprehension of complex sentences requires analysis of whole scenarios depending on phonological, syntactic and semantic entities in time. This can also be monitored by EEG-analysis. The demands of the working memory in both frontal hemispheres can even be observed during sentence processing. EEG coherence analysis would seem to be an important tool in investigation of the physiology of language representation.






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