Second, this collection of cognitive programs evolved in the Pleistocene to solve the adaptive problems regularly faced by our hunter-gatherer ancestors-...

This chapter defends the positive thesis which constitutes its title. It argues first, that the mind has been shaped by natural selection; and second, that the result of that shaping process is a modular mental architecture. The arguments presented are all broadly empirical in character, drawing on evidence provided by biologists, neuroscientists and psychologists (evolutionary, cognitive, and developmental), as well as by researchers in artificial intelligence. Yet the conclusion is at odds with the manifest image of ourselves provided both by (...) introspection and by common-sense psychology. The chapter concludes by sketching how a modular architecture might be developed to account for the patently unconstrained character of human thought, which has served as an assumption in a number of recent philosophical attacks on mental modularity. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

'Is there any other point to which you would wish to draw my attention?' 'To the curious incident of the dog in the night-time.' 'The dog did nothing in the night-time.' 'That was the curious incident, ' remarked Sherlock Holmes. The quotation from A. Conan Doyle with which this book begins, is a delightfully appropriate summation of the authors' point of view garnered from their fifteen years of experiments on the psychology of reasoning. Dr. Wason and Dr. Johnson-Laird are intrigued (...) by the extent to which most individuals can be considered naturally rational thinkers. They present here the surprising results of their comprehensive investigations of how humans draw explicit conclusions from evidence. Given a set of assertions, the authors write, to what extent can the individual appreciate all that follows from them by virtue of logic alone, and remain unseduced by plausible, but fallacious conclusions? We are not concerned with whether these assertions are true or false, nor with whether the individual holds them among his beliefs, nor with whether they are sane or silly. At the core of the Psychology of Reasoning is a vigorous discussion that incorporates various illustrations--some of them humorous, all of them fascinating--of the use of reason under a wide variety of different conditions. Particular emphasis is placed on the difficulties involved in dealing with negatively marked information that must be combined and used with other information for reaching conclusions. Thorough treatment is given as well to the search for plausible contexts that will render anomalous or ambiguous statements sensible. The authors have strived to isolate the components ofinference, the basic steps of any kind of deductive activity, in order to determine the psychological processes involved in them. What has been the outcome of this research? Dr. Wason and Dr. Johnson-Laird conclude, our research has suggested that the individual's logical competence may be either enhanced or limited by performance variables. And, of these, content has turned out to be vitally important for revealing, or obscuring structure. At best, we can all think like logicians; at worst, logicians all think like us. (shrink)

This paper will sketch a model of the human mind according to which the mind's structure is massively, but by no means wholly, modular. Modularity views in general will be motivated, elucidated, and defended, before the thesis of moderately massive modularity is explained and elaborated.

What is the relationship between common-sense, or 'folk', psychology and contemporary scientific psychology? Are they in conflict with one another? Or do they perform quite different, though perhaps complementary, roles? George Botterill and Peter Carruthers discuss these questions, defending a robust form of realism about the commitments of folk psychology and about the prospects for integrating those commitments into natural science. Their focus throughout the book is on the ways in which cognitive science presents a challenge to our common-sense self-image (...) - arguing that our native conception of the mind will be enriched, but not overturned, by science. The Philosophy of Psychology is designed as a textbook for upper-level undergraduate and beginning graduate students in philosophy and cognitive science, but as a text that not only surveys but advances the debates on the topics discussed, it will also be of interest to researchers working in these areas. (shrink)

In Mindblindness, Simon Baron-Cohen presents a model of the evolution and development of "mindreading." He argues that we mindread all the time, effortlessly, automatically, and mostly unconsciously. It is the natural way in which we interpret, predict, and participate in social behavior and communication. We ascribe mental states to people: states such as thoughts, desires, knowledge, and intentions. Building on many years of research, Baron-Cohen concludes that children with autism, suffer from "mindblindness" as a result of a selective impairment in (...) mindreading. For these children, the world is essentially devoid of mental things. Baron-Cohen develops a theory that draws on data from comparative psychology, from developmental, and from neuropsychology. He argues that specific neurocognitive mechanisms have evolved that allow us to mindread, to make sense of actions, to interpret gazes as meaningful, and to decode "the language of the eyes." A Bradford Book. (shrink)

Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)

In this classic, the world's expert on language and mind lucidly explains everything you always wanted to know about language: how it works, how children learn it, how it changes, how the brain computes it, and how it evolved. With deft use of examples of humor and wordplay, Steven Pinker weaves our vast knowledge of language into a compelling story: language is a human instinct, wired into our brains by evolution. The Language Instinct received the William James Book Prize from (...) the American Psychological Association and the Public Interest Award from the Linguistics Society of America. This edition includes an update on advances in the science of language since The Language Instinct was first published. (shrink)

There has been much interest in the possibility of connectionist models whose representations can be endowed with compositional structure, and a variety of such models have been proposed. These models typically use distributed representations that arise from the functional composition of constituent parts. Functional composition and decomposition alone, however, yield only an implementation of classical symbolic theories. This paper explores the possibility of moving beyond implementation by exploiting holistic structure-sensitive operations on distributed representations. An experiment is performed using Pollack’s Recursive (...) Auto-Associative Memory. RAAM is used to construct distributed representations of syntactically structured sentences. A feed-forward network is then trained to operate directly on these representations, modeling syn- tactic transformations of the represented sentences. Successful training and generalization is obtained, demonstrating that the implicit structure present in these representations can be used for a kind of structure-sensitive processing unique to the connectionist domain. (shrink)

The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule- based reasoning and whether they involve distributed or localist representations. The bene®ts and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used (...) for cognitive modelling. q 2001 Elsevier Science Ltd. All rights reserved. (shrink)

Parallel distributed processing is transforming the field of cognitive science. Microcognition provides a clear, readable guide to this emerging paradigm from a cognitive philosopher's point of view. It explains and explores the biological basis of PDP, its psychological importance, and its philosophical relevance.

Working memory limits are best defined in terms of the complexity of the relations that can be processed in parallel. Complexity is defined as the number of related dimensions or sources of variation. A unary relation has one argument and one source of variation; its argument can be instantiated in only one way at a time. A binary relation has two arguments, two sources of variation, and two instantiations, and so on. Dimensionality is related to the number of chunks, because (...) both attributes on dimensions and chunks are independent units of information of arbitrary size. Studies of working memory limits suggest that there is a soft limit corresponding to the parallel processing of one quaternary relation. More complex concepts are processed by or In segmentation, tasks are broken into components that do not exceed processing capacity and can be processed serially. In conceptual chunking, representations are to reduce their dimensionality and hence their processing load, but at the cost of making some relational information inaccessible. Neural net models of relational representations show that relations with more arguments have a higher computational cost that coincides with experimental findings on higher processing loads in humans. Relational complexity is related to processing load in reasoning and sentence comprehension and can distinguish between the capacities of higher species. The complexity of relations processed by children increases with age. Implications for neural net models and theories of cognition and cognitive development are discussed. (shrink)

Human cognition is said to be systematic: cognitive ability generalizes to structurally related behaviours. The connectionist approach to cognitive theorizing has been strongly criticized for its failure to explain systematicity. Demonstrations of generalization notwithstanding, I show that two widely used networks (feedforward and recurrent) do not support systematicity under the condition of local input/output representations. For a connectionist explanation of systematicity, these results leave two choices, either: (1) develop models capable of systematicity under local input/output representations; or (2) justify the (...) choice of similarity-based (nonlocal) component representations sufficient for systematicity. (shrink)

The following values have no corresponding Zotero field: PB - Lawrence Erlbaum Associates Ltd Hove,, UK.

This paper will sketch a model of the human mind according to which the mind’s structure is massively, but by no means wholly, modular. Modularity views in general will be motivated, elucidated, and defended, before the thesis of moderately massive modularity is explained and elaborated.

At root, the systematicity debate over classical versus connectionist explanations for cognitive architecture turns on quantifying the degree to which human cognition is systematic. We introduce into the debate recent psychological data that provides strong support for the purely structure-based generalizations claimed by Fodor and Pylyshyn (1988). We then show, via simulation, that two widely used connectionist models (feedforward and simple recurrent networks) do not capture the same degree of generalization as human subjects. However, we show that this limitation is (...) overcome by tensor networks that support relational processing. (shrink)