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Proposal for a new B.S. in Cognitive Science at Rensselaer

Proposal for a new B.S. in Cognitive Science at Rensselaer

Cognitive science is the scientific study of the mind/brain as it relates to intelligence, reasoning, decision making, memory, learning, language, perception, and action. This young and emerging interdisciplinary field lies at the intersection of psychology, computer science, philosophy, neuroscience, linguistics, and anthropology. Cognitive science promises to be the next ‘basic’ science, in line with physics, chemistry, and biology, as much of the research being conducted is aimed at discovering fundamental principles that underlie all minds, whether they are human minds, animal minds, or artificial minds. Further, just as the technologies based on physics, chemistry, and biology have had a tremendous impact on our lives, technology based on our understanding of cognitive systems has the potential to profoundly change the way we live and who we are. From using knowledge of human cognition to build ‘cognitively ergonomic’ tools and environments, to building devices to repair and augment cognitive skills and capacities, to creating artificially intelligent computers and robots, the applications of this discipline are right in line with Rensselaer’s rhetorical slogan ‘Why not change the world?’. We feel that the time is ripe to offer a B.S. in Cognitive Science, and that the Cognitive Science Department at Rensselaer is perfectly positioned to offer one of the very best degree programs of its kind in the world.
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Transcranial Theory of Mind: A New Revolution of Cognitive Science

Transcranial Theory of Mind: A New Revolution of Cognitive Science

With the development of 4E+S cognitive science, some philosophers have begun to believe that the location of cognition and the mind are not just in the brain. They can be extended outside of the brain. As Rowlands says, “Cognitive tasks are not, in general, the sort of thing that need be accomplished only in the head or by a brain” [1]. In general, the mind does not have a fixed size and may extend beyond the brain. Some of the philosophers say that the mind is embodied, some of them say it is extended, some of them say it is embedded, some of them say it is exacted, and some of them say it is situated. According to these sayings, the location of the mind can be in the body and in the environment. In other words, the mind is a complex set of states, processes, and activities distributed across the brain, body, and world. Mental states, processes, and activities may happen inside our brains, but they may also happen, partly, in our bodies outside our brains, and they may even happen, partly, in the world outside our bodies. This is why we also call 4E+S cognition “transcranial cognition” and “transbrain cognition”.
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Teaching Cognitive Science as Classics

Teaching Cognitive Science as Classics

It seems fair to claim that students of computing would be able more realistically to appreciate the nature of their professional work if they were given some understanding of how the human mind works, and some inkling of its superlative richness and variety. To help induce such ap- preciation, I have thus for some years been teaching two optional cognitive science units, one at third year level, one at honours level, the first a prerequisite for the second. These units are taught through four class contact hours a week over a fourteen week semester, two hours lecture per week and two hours seminar.
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Social Constructionism as Cognitive Science

Social Constructionism as Cognitive Science

Lurking within the linguistic turn is a potential for relativism, a complete denial of objective reality outside of language, for how can we determine when something is more than a mere cultural idea other than through the use of more linguistic behaviour? Much has been written about the nature of the ontological commitments of social constructionism focusing upon the degrees of realism that are acceptable in psychology (Parker, 1999; Potter, Edwards & Ashmore, 1999; McLennan, 2001; Still, 2001). Some theorists (for example, Gergen, 2001) directly criticize what they see as misguided realism in disciplines that have not taken the linguistic turn, such as cognitive science. In so doing, such theorists seek to undermine the fabric of that discipline. As a cognitive scientist I have read such arguments in a mood of some disquiet, not because I distrust my own particular views on realism, but because I recognize that the emphasis upon human cultural behaviour and its effects upon psychology is a research agenda for my discipline too (see Harré, 2002a). I have therefore been perplexed by the move from recognition of the social construction of cultural artefacts (by which I mean anything from technologies through to concepts) to a deep scepticism about the psychological dispositions that allow this to happen. What is more, as Harré (2002a) makes clear, it is crucial for cognitive science to understand humans as symbol users, for example at the linguistic level, and this means that any knowledge of the machinery that underlies human symbolic behaviour must pay heed to the normative “rules” of symbol use. An integrated science of mind and socially embedded action is required. To this end, I have wanted to outline the common interests of both social constructionism and cognitive science, in abstract theoretical terms, in order to facilitate future research and also to slice through the debates about ontology without simply making a position statement from the realist bench. The key to achieving this, I think, is in realizing that both groups are dealing with information systems and this paper aims to explicate this and its consequences.
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Almost a decade of Cognitive Science at Sheffield

Almost a decade of Cognitive Science at Sheffield

When the degree was first established, our aim was to train students in a wide range of methodological skills in psychology, computing, and mathematics. In practice, we have found methods training to be one of the most prob- lematic areas of the degree. The acquisition of program- ming skills has always proved difficult for a minority of our students and has lead to a significant number leaving the course (generally in the first year). To counteract this problem we have, over several years, reduced the amount of core training in computing methods. The question of whether Cognitive Science students should be trained in software design skills in addition to basic programming has also been a subject of some contention. This issue highlights a problem of teaching a degree which, to some extent, is like a dual honours, but in other ways is trying to target a specific mix of interdisciplinary skills (i.e. those required for computational modelling). Software design is clearly an important subject for students who go on to further training or employment in computing, how- ever, it seems only tangentially related to the core subject matter of Cognitive Science (whatever that may be!). After much deliberation this subject was finally dropped from the core curriculum in 1997 to make way for (what was felt to be) more directly relevant material. Mathe-
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An Introductory CS Course for Cognitive Science Students

An Introductory CS Course for Cognitive Science Students

requirement has until recently represented a serious de- ficiency of the program. This is especially ironic given the importance placed on the notion of computation as an organizing principle in modern cognitive science’s conception of the mind. One could argue that the funda- mental difference between cognitive science and other closely related fields such as cognitive psychology is the former’s emphasis on viewing human cognitive pro- cesses as a type of computation, and on building explicit models of these processes in the form of computer pro- grams. Furthermore, computation plays an important role in the philosophy of mind, with philosophical ar- guments and debates about the mind-body problem of- ten assuming a firm grasp of Turing machines and their properties. Students graduating with a major in cogni- tive science need to have more than just a passing ac- quaintance with these ideas, and ought to understand, on a basic level gained through firsthand experience, what it means to design, implement, and evaluate com- putational models of cognition.
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Contextuality: A Philosophical Paradigm,
with Applications to Philosophy of Cognitive Science

Contextuality: A Philosophical Paradigm, with Applications to Philosophy of Cognitive Science

There has been a wide debate in philosophy of cognitive science on the question “where is the mind?”. Apart from people whose context leads them to say that the question is malformed (i.e. people that restrict the word “where” to physical places), the literature has been divided mainly into two streams: people defending that the mind is only in the brain (individualists, e.g. Butler, 1998; Adams and Aizawa, 2001), and people defending that the mind is in the brain, body, and world (active externalists, e.g. Varela, 1994; Clark, 1997; Clark and Chalmers, 1998; Haugeland, 1998). We would explain the arid debate because, broadly, the people of each band are in different contexts. The main difference between them, is their concept of mind.
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An Approach to Philosophy of Cognitive Science

An Approach to Philosophy of Cognitive Science

From 1956 and through the 1960s, discussion in analytic philosophy of mind concerned competing theses about the metaphysics of mind – Gilbert Ryle’s behaviourism, the materialism of U.T. Place, Jack Smart, and David Armstrong, Hilary Putnam’s machine functionalism, and the rather different version of functionalism developed by David Lewis. 1 The 1960s also saw the publication of books by three of the most major figures in the philosophy of cognitive science. Chomsky’s Aspects of the Theory of Syntax was published in 1965, with its striking claim about cognitive states that are inaccessible to consciousness, states of tacit knowledge of syntactic rules (1965, p. 8): ‘Obviously, every speaker of a language has mastered and internalized a generative grammar that expresses his knowledge of his language. This is not to say that he is aware of the rules of the grammar or even that he can become aware of them.’ In 1968, Jerry Fodor published his first book, Psychological Explanation: An Introduction to the Philosophy of Psychology, along with an important paper, ‘The appeal to tacit knowledge in psychological explanations’. And Daniel Dennett’s Content and Consciousness, with its distinction between personal and subpersonal levels of description, appeared in 1969.
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Bayesian Cognitive Science, Unification, and Explanation

Bayesian Cognitive Science, Unification, and Explanation

An assumption often implicit in this literature is that unification obviously bears on explanation. Griffiths et al. ([2010], p. 360), for example, claim that ‘probabilistic models provide a unifying framework for explaining the inferences that people make in different settings.’ Clark ([2013], p. 201) writes that ‘one way to think about the primary ‘added value’ of these [kinds of Bayesian] models is that they bring perception, action, and attention into a single unifying framework. They thus constitute the perfect explanatory partner… for recent approaches that stress the embodied, environmentally embedded, dimensions of mind and reason’ (emphasis added). Even more explicit is Friston ([2009], [2010]). He suggests that the unification afforded to cognitive science by the Bayesian framework might be driven by a specific hypothesis, which he calls the “free-energy principle,” concerning how different phenomena are brought about by a single type of mechanism. Friston writes: ‘If one looks at the brain as implementing this scheme (minimising a variational bound on disorder), nearly every aspect of its anatomy and physiology starts to make sense’ (Friston [2009], p. 293); ‘a recently proposed free-energy principle for adaptive systems tries to provide a unified account of action, perception and learning... the principle [can] account for many aspects of brain structure and function and lends it the potential to unify different perspectives on how the brain works’ (Friston [2010], p. 127). Along the same lines, Hohwy ([2013], p. 1)
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Kant’s Emergence and Sellarsian Cognitive Science

Kant’s Emergence and Sellarsian Cognitive Science

The paper argues, against current views that see Kant as giving abstract descriptions of cognitive me- chanisms (after the fashion of functionalism in cognitive science), that Kant sees mental phenomena as akin to emergent phenomena in a sense traditionally opposed to mechanism. After distinguishing several relevant notions of emergence, the paper distinguishes several of Kant’s basic emergentist theses, includ- ing his emergent materialism in chemistry and a species of mental emergence modelled on that chemical emergence. However, Kant’s doctrine of the epigenesis of pure Reason is argued to be Kant’s most fun- damental emergentist thesis. The paper argues that Kant’s notion of mental emergence sheds light on some very puzzling aspects of his remarks about the unity of intuition and concept emphasized by Wilfrid Sellars. The paper sketches some of the problems in contemporary cognitive science and shows how a Sellarsian emergentism inspired by Kant addresses some of these problems and provides an interesting alternative to the kind of mechanistic positions that have tended to dominate the field. Finally, the paper locates the present emergentist reading with respect to the perspectivist reading of Kant.
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Crowdsourcing samples in cognitive science

Crowdsourcing samples in cognitive science

Across fields, research using online labor markets has typically taken the form of short, cross-sectional surveys conducted across the entire crowd population or on a speci fi c geographic subpopulation (e.g., US residents). However, online labor markets are fairly fl exible, and allow creative and sophisticated research methods (Box 2) limited only by the imaginations of researchers and their willingness to learn basic computer programming (Box 3). Accurate timing allows a wide range of paradigms from cognitive science to be implemented online (Box 4). Recently, several new tools (e.g., TurkPrime) and competitor marketplaces have developed more advanced sampling features while lowering technical barriers substantially.
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Analysis of Brain Activity using Cognitive Science and Machine Learning

Analysis of Brain Activity using Cognitive Science and Machine Learning

This research gives an insight into the thought process of human mind using various techniques of Artificial Intelligence. Various patterns are produced in the human mind according to the various kinds of thoughts going on in the mind. Through this research work based on Cognitive Science, we have tried to analyse few of those patterns or brain waves produced while feeling different kinds of emotions.

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Cognitive Science and Psychology

Cognitive Science and Psychology

What may be included in the mentalese are (a) recursive phrase-structure rules (e.g., S -> NP + VP), (b) transformation rules (e.g., applying a passive transformation to a predicate in mentalese results in an assertion which would be a passive sentence in L), (c) primitive operations, or primitives (e.g., the truth rules in Fodor's, 1975, language of thought), (d) non-standard rules of inference whose function is to reduce the demands on the central processor by increasing the burden of the long-term memory store (e.g., the meaning postulates which "do the work that definitions have usually been supposed to do" [Fodor, 1975, p. 149]), and (e) a vocabulary as extensive as that of L (Fodor, 1975). In short, a theory of mind in cognitive science is a specification of the functional
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Nervous Aesthetics: Cognitive Science, Literary Criticism and the Modern Novel

Nervous Aesthetics: Cognitive Science, Literary Criticism and the Modern Novel

Having said this, where scientific approaches are introduced to the humanities there exists the potential pitfall of reductionism in the application of theory and the subsequent analysis. By reductionism what is meant specifically is the habit of discussing a complex phenomenon entirely in terms of the simplest elements it can be distilled down to: for instance, while describing sexual attraction as ‘chemistry’ is merely shorthand, to discuss the phenomenon of sexual attraction in its entirety as a product merely of chemical processes within the brain is a reductionist approach. Chapters One and Two offer some more direct examples of how this narrow approach yields some almost farcically simplistic explanations for the appeal of the arts. The objective of this thesis, however, is not to reduce the appreciation of literature to a psychological or neurological phenomenon, nor to directly substitute science for literary theory. It is best understood as an interdisciplinary method of inquiry aimed extending the literary critic’s toolbox by borrowing from cognitive science. This has the potential to unlock new interpretations in literary criticism, and to give older and more intuitive ones a newfound clarity. Most importantly, it is aimed at empowering the reader by giving them the tools to explain and articulate their aesthetic reactions to a text.
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Radical Embodied Cognitive Science and Problems of Intentionality

Radical Embodied Cognitive Science and Problems of Intentionality

For their part, objectors might doubt that the concept of intentionality provides great illumination here. Why not simply say that cognition consists in interacting with the environment in interest-driven ways? What does it add to say that this creates about-ness? A second objection, as far as it goes, is that the view on offer arguably does relinquish the idea that teleosemiotics serves the purposes of cognitive science, given that the latter seems primarily concerned with explaining abilities. However, perhaps these objections can be met. One interesting possibility is that framing matters in terms of intentionality serves as a bridge between (a) biological and information-theoretic descriptions of agents and (b) more colloquial characterizations. And as for the second problem, Hutto and Myin claim that the explanation problem poses little danger to teleosemantics, because teleosemantics is not out to serve the purposes of cognitive science in the first place (pp. 111–2). So, perhaps they would happily concede the same for teleosemiotics. At any rate, I leave further development of this intriguing position to advocates of REC.
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A Cognitive Science Based Machine Learning Architecture

A Cognitive Science Based Machine Learning Architecture

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, human- like learning mechanisms: 1) perceptual learning, the learning of new objects, categories, relations, etc., 2) episodic learning of events, the what, where, and when, 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence.
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Cognitive science: From computers to anthills as models of human thought

Cognitive science: From computers to anthills as models of human thought

Also in 1956, the psychologist George Miller published an article with the title "The magical number seven, plus or minus two: some limits on our capacity for processing information" that has become a classic within cognitive science. Miller argued that there are clear limits to our cognitive capacities: we can actively process only about seven units of information. This article is noteworthy in two ways. First, it directly applies Shannon's information theory to human thinking. Second, it explicitly talks about cognitive processes, something which had been considered to be very bad manners in the wards of the behaviourists that were sterile of anything but stimuli and responses. However, with the advent of computers and information theory, Miller now had a mechanism that could be put in the black box of the brain: computers have a limited processing memory and so do humans.
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Animal Consciousness as a Test Case of Cognitive Science

Animal Consciousness as a Test Case of Cognitive Science

In our dealings with animals at least most of us see them as conscious beings. We say “the dog feels pain” ascribing sensation. We notice “My cat wants to get in the kitchen because she thinks there is some cheese left” ascribing beliefs and desires. On the other hand the employment of human catego- ries to animals seems to be problematic. Reflecting on the details of human beliefs, for example, casts serious doubt on whether the cat is able to believe anything at all. These theses try to reflect on methodological issues when investigating animal minds. Developing a theory of animal mentality seems to be a test case of the interdisciplinary research programme in cognitive science. From the philosopher`s perspective the most pressing problem is how to talk about animal minds. Can we just employ the vocabulary of human psychology? If not, exploring animal minds contains the non-trivial task of introducing a terminology that allows to see the distinctness of animal minds and to see its connection to the human case. Dealing with that problem can by a genuine job for a philosopher of (animal) mind in cognitive science. So the title “animal consciousness” may be a misnomer to start with. Speaking of “animals” without qualification is another misnomer. Within the animal kingdom we should expect quite different cognitive abilities. An ape may do what a monkey can`t, a monkey what a mouse can`t, a mouse what a tuna can`t … up to insects or some phyla where there is no mind at all. So we have to pay attention to this as well.
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Can Cognitive Science Improve the Training of Industrial Process Operators?

Can Cognitive Science Improve the Training of Industrial Process Operators?

Considerable research is still required before cognitive science can have any certainty about the cognitive processes involved when an opera- tor undertakes a complex dynamic task. Until there is this certainty, any training program will have to rely upon patterns of errors to ensure ef- fective design strategies, and the assessment of operator performance against models of expert behavior to measure improvement. Plant simula- tors would appear to be an ideal tool for carrying out this research. They offer the facility for pre- senting operators with a range of complex tasks. These tasks could be controlled by the researcher and would be repeatable. By making video re- cordings of the operators undertaking the tasks, a detailed analysis of the implied cognitive pro- cesses could be made. However, research would first have to show if the influences of being within a simulated environment significantly af- fected the cognitive processes of the operator when compared to studies carried out with opera- tors undertaking tasks within a real plant.
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MA IN COGNITIVE SCIENCE (TAUGHT IN ENGLISH)

MA IN COGNITIVE SCIENCE (TAUGHT IN ENGLISH)

The program trains specialists in the interdisciplinary field of Cognitive Science. Courses such as: Cognitive Psychology, Cognitive Modeling, Constructive Memory, Psychophysiological Studies and Cognitive Processes, Information Processing in the Human Brain, Psychophysics, Psycholinguistics are included in the program.

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