The Turing Test, originally proposed as a simple operational definition of intelligence, has now been with us for exactly half a century. It is safe to say that no other single article in computer science, and few other articles in science in general, have generated so much discussion. The present article chronicles the comments and controversy surrounding Turing's classic article from its publication to the present. The changing perception of the Turing Test over the last fifty years has paralleled the (...) changing attitudes in the scientific community towards artificial intelligence: from the unbridled optimism of 1960's to the current realization of the immense difficulties that still lie ahead. I conclude with the prediction that the Turing Test will remain important, not only as a landmark in the history of the development of intelligent machines, but also with real relevance to future generations of people living in a world in which the cognitive capacities of machines will be vastly greater than they are now. (shrink)

Implicit Learning and Consciousness challenges conventional wisdom and presents the most up-to-date studies to define, quantify and test the predictions of the main models of implicit learning. The chapters include a variety of research from computer modeling, experimental psychology and neural imaging to the clinical data resulting from work with amnesics. The result is a topical book that provides an overview of the debate on implicit learning, and the various philosophical, psychological and neurological frameworks in which it can be placed. (...) It will be of interest to undergraduates, postgraduates and the philosophical, psychological and modeling research community. (shrink)

Núñez and colleagues (2019) chronicle in extraordinary detail the “demise” of cognitive science, as it was first defined in the late 1970s. The problem is that their account, however accurate, misses the forest for the trees. Cognitive science circa 2019 is alive and well; it just has not followed the path anticipated by its founders over 40 years ago.

No computer that had not experienced the world as we humans had could pass a rigorously administered standard Turing Test. We show that the use of “subcognitive” questions allows the standard Turing Test to indirectly probe the human subcognitive associative concept network built up over a lifetime of experience with the world. Not only can this probing reveal differences in cognitive abilities, but crucially, even differences in _physical aspects_ of the candidates can be detected. Consequently, it is unnecessary to propose (...) even harder versions of the Test in which all physical and behavioral aspects of the two candidates had to be indistinguishable before allowing the machine to pass the Test. Any machine that passed the “simpler” symbols- in/symbols-out test as originally proposed by Turing would be intelligent. The problem is that, even in its original form, the Turing Test is already too hard and too anthropocentric for any machine that was not a physical, social, and behavioral carbon copy of ourselves to actually pass it. Consequently, the Turing Test, even in its standard version, is not a reasonable test for general machine intelligence. There is no need for an even stronger version of the Test. (shrink)

David Marr's (1982) three‐level analysis of computational cognition argues for three distinct levels of cognitive information processing—namely, the computational, representational, and implementational levels. But Marr's levels are—and were meant to be—descriptive, rather than interactive and dynamic. For this reason, we suggest that, had Marr been writing today, he might well have gone even farther in his analysis, including the emergence of structure—in particular, explicit structure at the conceptual level—from lower levels, and the effect of explicit emergent structures on the level (...) (or levels) that gave rise to them. The message is that today's cognitive scientists need not only to understand how emergent structures—in particular, explicit emergent structures at the cognitive level—develop but also to understand how they feed back on the sub‐structures from which they emerged. (shrink)

Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models (...) to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. (shrink)

What new implications does the dynamical hypothesis have for cognitive science? The short answer is: None. The _Behavior and Brain Sciences _target article, “The dynamical hypothesis in cognitive science” by Tim Van Gelder is basically an attack on traditional symbolic AI and differs very little from prior connectionist criticisms of it. For the past ten years, the connectionist community has been well aware of the necessity of using (and understanding) dynamically evolving, recurrent network models of cognition.

Relational priming is argued to be a deeply inadequate model of analogy-making because of its intrinsic inability to do analogies where the base and target domains share no common attributes and the mapped relations are different. Leech et al. rely on carefully handcrafted representations to allow their model to make a complex analogy, seemingly unaware of the debate on this issue fifteen years ago. Finally, they incorrectly assume the existence of fixed, context-independent relations between objects.

High-level perception--”the process of making sense of complex data at an abstract, conceptual level--”is fundamental to human cognition. Through high-level perception, chaotic environmen- tal stimuli are organized into the mental representations that are used throughout cognitive pro- cessing. Much work in traditional artificial intelligence has ignored the process of high-level perception, by starting with hand-coded representations. In this paper, we argue that this dis- missal of perceptual processes leads to distorted models of human cognition. We examine some existing artificial-intelligence models--”notably (...) BACON, a model of scientific discovery, and the Structure-Mapping Engine, a model of analogical thought--”and argue that these are flawed pre- cisely because they downplay the role of high-level perception. Further, we argue that perceptu- al processes cannot be separated from other cognitive processes even in principle, and therefore that traditional artificial-intelligence models cannot be defended by supposing the existence of a --œrepresentation module--� that supplies representations ready-made. Finally, we describe a model of high-level perception and analogical thought in which perceptual processing is integrated with analogical mapping, leading to the flexible build-up of representations appropriate to a given context. (shrink)

This book is an excellent manifesto for future work in child development. It presents a multidisciplinary approach that clearly demonstrates the value of integrating modeling, neuroscience, and behavior to explore the mechanisms underlying development and to show how internal context-dependent representations arise and are modified during development. Its only major flaw is to have given short shrift to the study of the role of genetics on development.

Green's target article is an attack on most current connectionist models of cognition. Our commentary will suggest that there is an essential component missing in his discussion of modeling, namely, the idea that the appropriate level of the model needs to be specified. We will further suggest that the precise form of connectionist networks will fall out as ever more detailed constraints are placed on their function.

The fixed-feature viewpoint Schyns et al. are opposing is not a widely held theoretical position but rather a working assumption of cognitive psychologists – and thus a straw man. We accept their demonstration of new-feature acquisition, but question its ubiquity in category learning. We suggest that new-feature learning (at least in adults) is rarer and more difficult than the authors suggest.

Natura non facit saltum (Nature does not make leaps) was the lovely aphorism on which Darwin based his work on evolution. It applies as much to the formation of mental representations as to the formation of species, and therein lies our major disagreement with the SOC model proposed by Perruchet & Vinter.

Two categorization arguments pose particular problems for localist connectionist models. The internal representations of localist networks do not reflect the variability within categories in the environment, whereas networks with distributed internal representations do reflect this essential feature of categories. We provide a real biological example of perceptual categorization in the monkey that seems to require population coding (i.e., distributed internal representations).

Zuidema et al. illustrate how empirical AGL studies can benefit from computational models and techniques. Computational models can help clarifying theories, and thus in delineating research questions, but also in facilitating experimental design, stimulus generation, and data analysis. The authors show, with a series of examples, how computational modeling can be integrated with empirical AGL approaches, and how model selection techniques can indicate the most likely model to explain experimental outcomes.

While we agree that the frame problem, as initially stated by McCarthy and Hayes (1969), is a problem that arises because of the use of representations, we do not accept the anti-representationalist position that the way around the problem is to eliminate representations. We believe that internal representations of the external world are a necessary, perhaps even a defining feature, of higher cognition. We explore the notion of dynamically created context-dependent representations that emerge from a continual interaction between working memory, (...) external input, and long-term memory. We claim that only this kind of representation, necessary for higher cognitive abilities such as counterfactualization, will allow the combinatorial explosion inherent in the frame problem to be avoided. (shrink)

Taking to heart Massaro's [(1988) Some criticisms of connectionist models of human performance, Journal of Memory and Language, 27, 213-234] criticism that multi-layer perceptrons are not appropriate for modeling human cognition because they are too powerful (i.e. they can simulate just about anything, which gives them little explanatory power), Regier develops the notion of constrained connectionism. The model that he discusses is a distributed network but with numerous constraints added that are (more or less) motivated by real psychophysical and neurophysical (...) constraints. His model learns static prepositions of spatial location such as in, above, to the left of, to the right of, under, etc., as well as dynamic prepositions such as through and the Russian iz-pod, meaning out from under. The network learns these prepositions by viewing a number of examples of them. Very importantly, this book tackles-and goes a long way towards resolving-the problem of the lack of negative exemplars (i.e. we are only very rarely told when something is not above something else), which should lead to overgeneralization, but does not. This book is a significant contribution to connectionist literature. (shrink)

Are similar, or even identical, mechanisms used in the computational modeling of speech segmentation, serial image processing, and music processing? We address this question by exploring how TRACX2, a recognition‐based, recursive connectionist autoencoder model of chunking and sequence segmentation, which has successfully simulated speech and serial‐image processing, might be applied to elementary melody perception. The model, a three‐layer autoencoder that recognizes “chunks” of short sequences of intervals that have been frequently encountered on input, is trained on the tone intervals of (...) melodically simple French children's songs. It dynamically incorporates the internal representations of these chunks into new input. Its internal representations cluster in a manner that is consistent with “human‐recognizable” melodic categories. TRACX2 is sensitive to both contour and proximity information in the musical chunks that it encounters in its input. It shows the “end‐of‐word” superiority effect demonstrated by Saffran et al. (1999) for short musical phrases. The overall findings suggest that the recursive autoassociative chunking mechanism, as implemented in TRACX2, may be a general segmentation and chunking mechanism, underlying not only word‐ and image‐chunking, but also elementary melody processing. (shrink)

Three‐ to 4‐month‐old infants show asymmetric exclusivity in the acquisition of cat and dog perceptual categories. The cat perceptual category excludes dog exemplars, but the dog perceptual category does not exclude cat exemplars. We describe a connectionist autoencoder model of perceptual categorization that shows the same asymmetries as infants. The model predicts the presence of asymmetric retroactive interference when infants acquire cat and dog categories sequentially. A subsequent experiment conducted with 3‐ to 4‐month‐olds verifies the predicted pattern of looking time (...) behaviors. We argue that bottom‐up, associative learning systems with distributed representations are appropriate for modeling the operation of short‐term visual memory in early perceptual category learning. (shrink)

Starting with the hypothesis that analogical reasoning consists of a search of semantic space, we used eye-tracking to study the time course of information integration in adults in various formats of analogies. The two main questions we asked were whether adults would follow the same search strategies for different types of analogical problems and levels of complexity and how they would adapt their search to the difficulty of the task. We compared these results to predictions from the literature. Machine learning (...) techniques, in particular support vector machines (SVMs), processed the data to find out which sets of transitions best predicted the output of a trial (error or correct) or the type of analogy (simple or complex). Results revealed common search patterns, but with local adaptations to the specifics of each type of problem, both in terms of looking-time durations and the number and types of saccades. In general, participants organized their search around source-domain relations that they generalized to the target domain. However, somewhat surprisingly, over the course of the entire trial, their search included, not only semantically related distractors, but also unrelated distractors, depending on the difficulty of the trial. An SVM analysis revealed which types of transitions are able to discriminate between analogy tasks. We discuss these results in light of existing models of analogical reasoning. (shrink)

"M. F. Simone Roberts's A Poetics of Being-Two is animated by a lively and engaging voice, drawing readers in with a sense of serious purpose working (delightfully) in tandem with a sense of humor. Roberts's aesthetics and her close readings of Yves Bonnefoy, St-John Perse, and Jorie Graham clearly demonstrate the literary effectiveness of Irigarayan sexual difference as an analytic trope, even as they emphasize the philosophical and political possibilities sexual difference opens up for feminism, environmentalism, and all levels of (...) contemporary cultural critique and activism."—Gail M. Schwab, Hofstra University -/- In An Ethics of Sexual Difference, Irigaray calls for a new poetics in the sense of both art and life. Rather than a critique from within philosophy, A Poetics of Being-Two tests Irigaray's ethics by extending it to other sites of cultural production. Where Irigaray's method finds stirrings and repressions of sexual difference in philosophy, this project explores that tension in poetics. Building from Irigaray's ethics, the book describes a poetics of being-two as concerns gendered subjectivity in literary poetics and then traces the on-going emergence of a poetics of being-two in the post-symbolist poetic tradition. Irigaray scholars will be interested in the sustained interpolation of Irigaray's ethical concepts as principles for a critical aesthetics and in their hermeneutic application in reading a literary tradition. Readers in comparative literature will find the first sustained feminist engagements with the major French poets Bonnefoy and Perse and an elucidation of their influence on the Pulitzer Prize winning poet Jorie Graham. (shrink)

SummaryHeterozygous 4.1 hereditary elliptocytosis results from the absence of one haploid set of protein 4.1, a major component of the red cell skeleton. Two successive epidemiological investigations revealed fifteen probands in the French Northern Alps. The frequency of this disease seems to be very high in four small villages isolated in the Aravis mountains. The genealogical study shows that eleven probands share common ancestors who lived eight or ten generations ago in these villages. Thus there was probably a founder (...) effect from one pair of ancestors, strengthened by endogamy. In contrast, four probands originate from another area and are not genealogically related. Recent results in molecular genetics support the present data. (shrink)

We attempt to gain some insight into the issue of whether pure states evolve to density matrices in the black hole evaporation process by examining the mode functions of the particles entering the black hole which are correlated with the particles which escape to infinity. We show that these particles enter the black hole singularity at relatively early times. This tends to support the view that pure states evolve to density matrices, i.e., that in this process quantum coherence is lost.

ABSTRACTThis article discusses the French debate of the 1580s over the status of the Salic Law and its influence upon an important text in English political thought, Robert Persons’s Conference about the next Succession to the Crowne of Ingland. Polemicists on both sides of the conflict between Henri of Navarre and the Catholic League, from Pierre de Belloy to the pseudonymous ‘Rossaeus’, sought to explain the French royal succession using a concept of custom drawn from Roman law. (...) Custom offered these thinkers a way to explain the Salic Law’s peculiar limitation of the succession to males descended agnatically, but it could also be taken to imply that the people, from whom it originated, were in some way superior to the king. The concept was exploited most effectively by Rossaeus, who translated what had been a legal discourse into a freer language of political naturalism. Rossaeus’s interpretation of custom was adapted and exploited by Robert Persons in the Conference about the next Succession to the Crowne of Ingland. While, then, much of the Conference’s contemporary influence derived from how its argument mapped onto English constitutional geography, it originated as a continuation of League political thought. (shrink)

This book shows that the repeated announcements of the death of Hegel's philosophical system have been premature. Hegel's Philosophy of Freedom, Reality, and God brings to light accomplishments for which Hegel is seldom given credit: unique arguments for the reality of freedom, for the reality of knowledge, for the irrationality of egoism, and for the compatibility of key insights from traditional theism and naturalistic atheism. The book responds in a systematic manner to many of the major criticisms leveled at Hegel's (...) system, from Feuerbach and Kierkegaard to Heidegger and Charles Taylor. It provides detailed interpretations of Hegel's Philosophy of Spirit, large parts of his indispensable Science of Logic, and important parts of his Philosophy of Nature and Philosophy of Right. Unlike many academic books on Hegel, this one treats him very much as a 'live' thinker, whom we can learn from today. (shrink)

This is a book-length study of two of Descartes's most innovative successors, Robert Desgabets and Pierre-Sylvain Regis, and of their highly original contributions to Cartesianism. The focus of the book is an analysis of radical doctrines in the work of these thinkers that derive from arguments in Descartes: on the creation of eternal truths, on the intentionality of ideas, and on the soul-body union. As well as relating their work to that of fellow Cartesians such as Malebranche and Arnauld, (...) the book also establishes the important though neglected role played by Desgabets and Regis in the theologically and politically charged reception of Descartes in early modern France. This is a major contribution to the history of Cartesianism that will be of special interest to historians of early modern philosophy and historians of ideas. (shrink)

It is not too great an exaggeration to claim that On the Origin of Species was, along with Das Kapital, one of the two most significant works in the intellectual history of the nineteenth century. As George Henry Lewes wrote in 1868, ‘No work of our time has been so general in its influence’. However, the very generality of the influence of Darwin’s work provides the chief problem for the intellectual historian. Most books and articles on the subject assert the (...) influence but remain very imprecise about its nature. It is very difficult indeed to assess what it was about the Darwinian theory which was so influential and how its influence was felt. This problem in Victorian intellectual history intersects with a related one in the history of science. There has been a tendency on the part of historians of science to isolate Darwin in two related ways. The first is to single him out from the mainstream of nineteenth-century naturalism in Britain and allow ‘Darwinism’ to stand duty for the wider movement of which it was in fact but a part. The second is the tendency to single out his evolutionary theory and to demarcate it sharply from those of his predecessors and contemporaries. According to this interpretation Darwin stood alone as a real, empirical scientist and provided the first genuinely scientific hypothesis for the process by which evolution might have occurred. The theories of the other main evolutionists—Erasmus Darwin, Lamarck, Chambers, Spencer, and Wallace—were more or less besmirched by ideological, anthropomorphic, or other ‘non-scientific’ factors or by the uses to which they were put by their authors. Charles Darwin is thus made to stand out as a figure of comparatively unalloyed scientific status and is treated in relative isolation from the social and intellectual context in which he worked and into which his theory was received. (shrink)