Although conditional stimulus (CS)/unconditional stimulus (US) contingency awareness appears to be necessary for human Pavlovian autonomie conditioning, only a selective review of the literature and the forgetting of certain basic, brute facts can allow the cognitive conclusion that awareness causes, or even is important for, conditioning. That conclusion is theoretically barren for explaining the phenomenon and is also of little potential practical use.

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...) mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation. (shrink)

The theory of embodied cognition can provide HCI practitioners and theorists with new ideas about interac-tion and new principles for better designs. I support this claim with four ideas about cognition: (1) interacting with tools changes the way we think and perceive – tools, when manipulated, are soon absorbed into the body schema, and this absorption leads to fundamental changes in the way we perceive and conceive of our environments; (2) we think with our bodies not just with our brains; (...) (3) we know more by doing than by seeing – there are times when physically performing an activity is better than watching someone else perform the activity, even though our motor resonance system fires strongly during other person observa-tion; (4) there are times when we literally think with things. These four ideas have major implications for interaction design, especially the design of tangible, physical, context aware, and telepresence systems. (shrink)

We argue that existing learning algorithms are often poorly equipped to solve problems involving a certain type of important and widespread regularity that we call “type-2 regularity.” The solution in these cases is to trade achieved representation against computational search. We investigate several ways in which such a trade-off may be pursued including simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription.”.

O'Brien & Opie's (O&O's) theory demands a view of unconscious processing that is incompatible with virtually all current PDP models of neural activity. Relative to the alternatives, the theory is closer to an AI than a parallel distributed processing (PDP) perspective, and its treatment of phenomenology is ad hoc. It raises at least one important question: Could features of network relaxation be the “switch” that turns an unconscious into a conscious network?

This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated (...) semantically. I criticize the reasons in support of this view and its presupposition of representation and semantics. Furthermore, I argue that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicit intrinsic representations. (shrink)

Minds are said to be systematic: the capacity to entertain certain thoughts confers to other related thoughts. Although an important property of human cognition, its implication for cognitive architecture has been less than clear. In part, the uncertainty is due to lack of precise accounts on the degree to which cognition is systematic. However, a recent study on learning transfer provides one clear example. This study is used here to compare transfer in humans and feedforward networks. Simulations and analysis show, (...) that while feedforward networks with shared weights are capable of exhibiting transfer, they cannot support the same degree of transfer as humans. One interpretation of these results is that common connectionist models lack explicit internal representations permitting rapid learning. (shrink)

The connectionist vehicle theory of phenomenal experience in the target article identifies consciousness with the brain’s explicit representation of information in the form of stable patterns of neural activity. Commentators raise concerns about both the conceptual and empirical adequacy of this proposal. On the former front they worry about our reliance on vehicles, on representation, on stable patterns of activity, and on our identity claim. On the latter front their concerns range from the general plausibility of a vehicle theory to (...) our specific attempts to deal with the dissociation studies. We address these concerns, and then finish by considering whether the vehicle theory we have defended has a coherent story to tell about the active, unified subject to whom conscious experiences belong. (shrink)

The implicit-explicit distinction is applied to knowledge representations. Knowledge is taken to be an attitude towards a proposition which is true. The proposition itself predicates a property to some entity. A number of ways in which knowledge can be implicit or explicit emerge. If a higher aspect is known explicitly then each lower one must also be known explicitly. This partial hierarchy reduces the number of ways in which knowledge can be explicit. In the most important type of implicit knowledge, (...) representations merely reflect the property of objects or events without predicating them of any particular entity The dearest cases of explicit knowledge of a fact are representations of one's own attitude of knowing that fact. These distinctions are discussed in their relationship to similar distinctions such as procedural-declarative, conscious unconscious, verbalizable-nonverbalizable, direct-indirect tests, and automatic voluntary control. This is followed by an outline of how these distinctions can be used to integrate and relate the often divergent uses of the implicit-explicit distinction in different research areas. We illustrate this for visual perception, memory, cognitive development, and artificial grammar learning. (shrink)

This paper investigates connectionism's potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism's distributed representations may look promising from this perspective, doubts can (...) be raised about the potential of distributed representations to allow large amounts of complexly structured information to be adequately encoded and processed. It is questionable whether connectionist models that are claimed to effectively represent structured information can be scaled up to a realistic extent. We conclude that the frame problem provides a difficulty to connectionism that is no less serious than the obstacle it constitutes for classical cognitive science. (shrink)

We present data and argument to show that in Tetris - a real-time interactive video game - certain cognitive and perceptual problems are more quickly, easily, and reliably solved by performing actions in the world rather than by performing computational actions in the head alone. We have found that some translations and rotations are best understood as using the world to improve cognition. These actions are not used to implement a plan, or to implement a reaction; they are used to (...) change the world in order to simplify the problem-solving task. Thus, we distinguish pragmatic actions ñ actions performed to bring one physically closer to a goal - from epistemic actions - actions performed to uncover information that is hidden or hard to compute mentally. To illustrate the need for epistemic actions, we first develop a standard information-processing model of Tetris-cognition, and show that it cannot explain performance data from human players of the game - even when we relax the assumption of fully sequential processing. Standard models disregard many actions taken by players because they appear unmotivated or superfluous. However, we describe many such actions that are actually taken by players that are far from superfluous, and that play valuable roles in improving human performance. We argue that traditional accounts are limited because they regard action as having a single function: to change the world. By recognizing a second function of action - an epistemic function - we can explain many of the actions that a traditional model cannot. Although, our argument is supported by numerous examples specifically from Tetris, we outline how the one category of epistemic action can be incorporated into theories of action more generally. (shrink)

A comprehensive introduction to the Language of Though Hypothesis (LOTH) accessible to general audiences. LOTH is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in (...) syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

To explain why, in scientific problem solving, a diagram can be “worth ten thousand words,” Jill Larkin and Herbert Simon (1987) relied on a computer model: two representations can be “informationally” equivalent but differ “computationally,” just as the same data can be encoded in a computer in multiple ways, more or less suited to different kinds of processing. The roots of this proposal lay in cognitive psychology, more precisely in the “imagery debate” of the 1970s on whether there are image-like (...) mental representations. Simon (1972, 1978) hoped to solve this debate by thoroughly reducing the differences between forms of mental representations (e.g., between images and sentences) to differences in computational efficiency; to carry out this reduction, he borrowed from computer science the concepts of data type and of data structure. I argue that, in the end, his account amounted to nothing more than characterizing representations by the fast operations on them. This analysis then allows me to assess what Simon’s approach actually achieves when transported from psychology to the study of scientific representations, as in Larkin and Simon (1987): it allows comparing, not representations in and of themselves, but rather the computational roles they play in particular problem-solving processes—that is, representations together with a particular way of using them. (shrink)

Are there representations in the brain? It depends on what you mean by representations, and it depends on what you want them to do for you—both in terms of the causal role they play in the system, and in terms of their explanatory value. But ideally, we would like an account of representation that allows us to assign a representational role and content to the appropriate mechanistic precursors of behavior that in fact play that role and conversely, search for the (...) mechanistic realizers of representational roles that are posited by our models of behavior and cognition. Such an account would be methodologically valuable in neuroscience. Lately, people have started asking similar questions about deep neural networks. What representations do they learn and use, and what is the relation between those representations and the sometimes impressive capacities these networks exhibit? More philosophically puzzling, perhaps, is the question of why the internal activities or dispositions labeled as such in neuroscience and AI research should count as representations at all. I think we can give a unified answer to both sets of questions, in the form of a kind of representational pragmatism. What makes something a representation just is that we can identify and re-identify it as such, and moreover, that we can manipulate it effectively to do whatever it is that we think representations ought to do for us in that particular context. For the first condition, the idea is that so long as we have some probe that allows us to pick out the relevant causally effective candidate, we should consider that to be a candidate representation-relative-to-that-probe. The second condition can be understood as a kind of anti-gerrymandering constraint: one ought to be able to intervene on the candidate, and see effects of that intervention consistent with the functional role the representation is supposed to play. Naturally the details need to be spelled out for different contexts—and I will articulate them for a few illustrative cases—which effectively allows for a kind of pluralism about representation depending on the setting and the kinds of questions being asked. With the extra components filled in, representational pragmatism can make sense of existing practices in neuroscience and AI, as well as their relationship to naturalistic theories of representation in philosophy. (shrink)

Among the cognitive capacities of evolved creatures is the capacity to represent. Theories in cognitive neuroscience typically explain our manifest representational capacities by positing internal representations, but there is little agreement about how these representations function, especially with the relatively recent proliferation of connectionist, dynamical, embodied, and enactive approaches to cognition. In this talk I sketch an account of the nature and function of representation in cognitive neuroscience that couples a realist construal of representational vehicles with a pragmatic account of (...) mental content. I call the resulting package a deflationary account of mental representation and I argue that it avoids the problems that afflict competing accounts. (shrink)

O'Brien & Opie do not address the question of the psychotherapeutic role of unconscious representational states such as beliefs. A dilemma is proposed: if they accept the legitimacy of such states then they should modify what they say about dissociation, and if they do not, they owe us an account of why.

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

Explicitness has usually been approached from two points of view, labelled by Kirsh the structural and the process view, that hold opposite assumptions to determine when information is explicit. In this paper, we offer an intermediate view that retains intuitions from both of them. We establish three conditions for explicit information that preserve a structural requirement, and a notion of explicitness as a continuous dimension. A problem with the former accounts was their disconnection with psychological work on the issue. We (...) review studies by Karmiloff-Smith, and Shanks and St. John to show that the proposed conditions have psychological grounds. Finally, we examine the problem of explicit rules in connectionist systems in the light of our framework. (shrink)

Block explains the conflation of phenomenal consciousness and access consciousness by appeal to the ambiguity of the term “consciousness.” However, the nature of ambiguity is not at all clear, and the thesis that “consciousness” is ambiguous between phenomenal consciousness and access consciousness is far from obvious. Moreover, the conflation can be explained without supposing that the term is ambiguous. Block's argument can thus be strengthened by avoiding controversial issues in the semantics of “consciousness.”.

This paper explores speakers'' epistemic access to the semanticand syntactic features of sentences of their language. I argue that there is evidence that ceteris paribus, the actual semantic features of sentences of a language are accessible as such by typical speakers of that language.I then explore various linguistic, cognitive, and epistemic consequences of this position.

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction 2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis? 2.2The informational benefits of multivariate pattern analysis 3Why the Decoder’s Dictum Is False 3.1We don’t know what information is decoded 3.2The theoretical basis for the dictum 3.3Undermining the theoretical basis 4Objections and Replies 4.1Does anyone really believe the dictum? 4.2Good decoding is not enough 4.3Predicting behaviour is not enough 5Moving beyond the Dictum 6Conclusion. (shrink)

Some regularities enjoy only an attenuated existence in a body of training data. These are regularities whose statistical visibility depends on some systematic recoding of the data. The space of possible recodings is, however, infinitely large – it is the space of applicable Turing machines. As a result, mappings that pivot on such attenuated regularities cannot, in general, be found by brute-force search. The class of problems that present such mappings we call the class of “type-2 problems.” Type-1 problems, by (...) contrast, present tractable problems of search insofar as the relevant regularities can be found by sampling the input data as originally coded. Type-2 problems, we suggest, present neither rare nor pathological cases. They are rife in biologically realistic settings and in domains ranging from simple animat behaviors to language acquisition. Not only are such problems rife – they are standardly solved! This presents a puzzle. How, given the statistical intractability of these type-2 cases, does nature turn the trick? One answer, which we do not pursue, is to suppose that evolution gifts us with exactly the right set of recoding biases so as to reduce specific type-2 problems to type-1 mappings. Such a heavy-duty nativism is no doubt sometimes plausible. But we believe there are other, more general mechanisms also at work. Such mechanisms provide general strategies for managing problems of type-2 complexity. Several such mechanisms are investigated. At the heart of each is a fundamental ploy – namely, the maximal exploitation of states of representation already achieved by prior, simpler learning so as to reduce the amount of subsequent computational search. Such exploitation both characterizes and helps make unitary sense of a diverse range of mechanisms. These include simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription”. In addition, the most distinctive features of human cognition – language and culture – may themselves be viewed as adaptations enabling this representation/computation trade-off to be pursued on an even grander scale. (shrink)

Two standard epistemological accounts are conflated in Dienes & Perner's account of knowledge, and this conflation requires the rejection of their four conditions of knowledge. Because their four metarepresentations applied to the explicit-implicit distinction are paired with these conditions, it follows by modus tollens that if the latter are inadequate, then so are the former. Quite simply, their account misses the link between true reasoning and knowledge.

In their article entitled “Ethical Particularism and Patterns”, Frank Jackson, Philip Pettit, and Michael Smith (JPS henceforth) argue that moral particularism is a cognitively implausible theory since it appears to entail the view that one might have a skill that is not grounded in an ability to recognise and represent natural patterns in the world. This charge echoes the complaints of computational theorists of cognition against their embodied cognition counterparts, namely that, theories of cognition that eschew talk of mental representation (...) are implausible qua theories of cognition. In both debates, the cognitive role of generalisation is central to the discussion; however, contrary to the received wisdom, I want to suggest that the dispute is not between generalisation or mental representation on the one hand and no generalisation or mental representation on the other, but rather between what I will call global and local generalisation. Using the dialogue between JPS and Dancy (our paradigm particularist) to frame this discussion, I show that by replacing Dancy's connectionist model for particularist reasoning with a case-based one, we not only vindicate his response to JPS, but we also gain insight into how it is the global/local distinction rather than the generalisation/no generalisation distinction that divides the two views. (shrink)

How do we find out whether someone is conscious of some information or not? A simple answer is “We just ask them”! However, things are not so simple. Here, we review recent developments in the use of subjective and objective methods in implicit learning research and discuss the highly complex methodological problems that their use raises in the domain.

Explicitness has usually been approached from two points of view, labelled by Kirsh the structural and the process view, that hold opposite assumptions to determine when information is explicit. In this paper, we offer an intermediate view that retains intuitions from both of them. We establish three conditions for explicit information that preserve a structural requirement, and a notion of explicitness as a continuous dimension. A problem with the former accounts was their disconnection with psychological work on the issue. We (...) review studies by Karmiloff-Smith, and Shanks and St. John to show that the proposed conditions have psychological grounds. Finally, we examine the problem of explicit rules in connectionist systems in the light of our framework. (shrink)

In the original target article (Shanks & St. John 1994), one of our principal conclusions was that there is almost no evidence that learning can occur outside awareness. The continuing commentaries raise some interesting questions, especially about the definition of learning, but do not lead us to abandon our conclusion.

Martínez-Manrique contends that we overlook a possible nonconnectionist vehicle theory of consciousness. We argue that the position he develops is better understood as a hybrid vehicle/process theory. We assess this theory and in doing so clarify the commitments of both vehicle and process theories of consciousness.

At present, the prevailing Connectionist methodology forrepresenting rules is toimplicitly embody rules in neurally-wired networks. That is, the methodology adopts the stance that rules must either be hard-wired or trained into neural structures, rather than represented via explicit symbolic structures. Even recent attempts to implementproduction systems within connectionist networks have assumed that condition-action rules (or rule schema) are to be embodied in thestructure of individual networks. Such networks must be grown or trained over a significant span of time. However, arguments (...) are presented herein that humanssometimes follow rules which arevery rapidly assignedexplicit internal representations, and that humans possessgeneral mechanisms capable of interpreting and following such rules. In particular, arguments are presented that thespeed with which humans are able to follow rules ofnovel structure demonstrates the existence of general-purpose rule following mechanisms. It is further argued that the existence of general-purpose rule following mechanisms strongly indicates that explicit rule following is not anisolated phenomenon, but may well be a common and important aspect of cognition. The relationship of the foregoing conclusions to Smolensky''s view of explicit rule following is also explored. The arguments presented here are pragmatic in nature, and are contrasted with thekind of arguments developed by Fodor and Pylyshyn in their recent, influential paper. (shrink)

This thesis is an examination and critique of naturalistic representational theories of phenomenal character. Phenomenal character refers to the distinctive quality that perceptual and sensational experiences seem to have; it is identified with 'what it is like' to undergo experiences. The central claims of representationalism are that phenomenal character is identical with the content of experience and that all representational states, bearing appropriate relations to the cognitive system, are conscious experiences. These claims are taken to explain both how conscious experiential (...) states arise and their nature. After examining the desiderata for naturalistic explanations, I argue that theories which ascribe nonconceptual content to experiences are the most plausible versions of representationalism. Further, causal covariation and teleological theories yield distinctive and interesting representationalist positions, hence, they become the focus of this study. To assess representationalism, I investigate whether all differences in phenomenal character can be correlated with differences in content. I claim that a useful distinction can be drawn between implicit and explicit content, which allows one to best describe the phenomena of perfect and relative pitch. I then argue that ambiguous figures show that two experiences can have the same content but different phenomenal character. I explicate the Inverted Earth hypothesis and claim that to identify content and phenomenal character, representationalists either have to condone the possibility of philosophical zombies, or hold that people lack authoritative first-person knowledge of their current experiences. Both these positions are unpalatable. Finally, I argue that representationalists cannot ascribe contents to experiences of novel colours to account for their phenomenal character. I also question, in light of dissociation phenomena, whether there is one distinctive relationship that all experiences bear to the cognitive system. I conclude that phenomenal character cannot be identical with the type of content under investigation, and that naturalistic representationalist theories cannot fully explain conscious experience. (shrink)

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. (shrink)

Various systems that learn are examined to show how content is carried in connections installed by a learning history. Agents do not explicitly use the content of such states in practical reasoning, yet the content plays an important role in explaining behavior, and the physical state carrying that content plays a role in causing behavior, given other occurrent beliefs and desires. This leads to an understanding of the environmental reasons which are the determinate content of these states, and leads to (...) a better grasp of how representational content can be carried by systems without an explicit representation. (shrink)

Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, (...) based upon the criterion ofconstant time processing.The present paper examines Kirsh''s claims. It is argued that Kirsh fails to demonstrate that our usage of explicit and implicit is seriously confused or inconsistent. Furthermore, it is argued that Kirsh''s new formulation of the explicit-implicit distinction is excessively stringent, in that it banishes virtually all sentences of natural language from the realm of explicit representation. By contrast, the present paper proposes definitions for explicit and implicit which preserve most of our strong intuitions concerning straightforward uses of these terms. It is also argued that the distinction delineated here sustains the meaningfulness of the abovementioned debate between classicists and connectionists. (shrink)

This paper aims at answering the question “When is informational content explicitly represented in a cognitive system?”. I first distinguish the explicitness this question is about from other kinds of explicitness that are currently investigated in philosophy of mind, and situate the components of the question within the various conceptual frameworks that are used to study mental representations. I then present and criticize, on conceptual and empirical grounds, two basic ways of answering the question, the first one coming from the (...) classical computational theory of mind, the latter one issued from a procedural conception of informational contents. I then argue for a new answer to the initial question, an answer that retains some valuable insights of the criticized theories, but which underlines the importance and the interpretational source of the distinctiveness proper to explicitly represented contents. (shrink)

Individual creativity is standardly treated as an ‘internalist’ process occurring solely in the head. An alternative, more interactionist view is presented here, where working with objects, media and other external things is seen as a fundamental component of creative thought. The value of chance interaction and chance cueing — practices widely used in the creative arts — is explored briefly in an account of the creative method of choreographer Wayne McGregor and then more narrowly in an experimental study that compared (...) performance on a Scrabble-like word discovery problem. Subjects were presented with seven letters and given two minutes to call out three-to-seven-letter English words. There were three conditions: The tiles were fixed in place, subjects were free to move the tiles manually or the tiles could be randomly shuffled. Results showed that random shuffling was best, with manual movement second. Three reasons are provided: Shuffling is faster and cheaper than mentally thinking of candidates; randomizing strings covers the search space better than a deterministic method based on past successes; and randomizing is equivalent to adding diversity to a team, which is known empirically to lead to more creative solutions. (shrink)

This paper is intended to sketch the definition of a methodological tool -- the notion of a format of representation -- for the study of scientific theorising. One of its main assumption is that a philosophical study of theorising needs to pay attention to other types of units of analysis than the traditional ones, namely, theories and models approached in a logical and structural way, since scientific reasoning is always led on concrete representational devices and depends upon their specific properties. (...) The notion of a format is intended to characterise the differences between various types of representational devices, in terms of the inferences they enable cognitive agents to draw. (shrink)

Shanks and St. John (1994a) suggest that From the viewpoint of a computer scientist who tries to construct learning systems, that claim seems rather implausible. In this commentary I wish to suggest why, in the hopes of shedding light on the relationship between consciousness and learning.

There is general agreement that from the first few months of life, our apprehension of physical objects accords, in some sense, with certain principles. In one philosopher's locution, we are 'perceptually sensitive' to physical principles describing the behavior of objects. But in what does this accordance or sensitivity consist? Are these principles explicitly represented or merely 'implemented'? And what sort of explanation do we accomplish in claiming that our object perception accords with these principles? My main goal here is to (...) suggest answers to these questions. I argue that the object principles are not explicitly represented, first addressing some confusion in the debate about what that means. On the positive side, I conclude that the principles supply a competence account, at Marr's computational level, and that they function like natural constraints in vision. These are among their considerable explanatory benefits - benefits endowed by rules and principles in other cognitive domains as well. Characterizing the explanatory role of the object principles is my main project here, but in pursuing certain sub-goals I am led to other conclusions of interest in their own right. I address an argument that the object principles are explicitly represented which assumes that object perception is substantially thought-like. This provokes a jaunt off the main path which leads to interesting territory: the boundary between thought and perception. I argue that object apprehension is much closer to perception than to thought on the spectrum between the two. (shrink)