We address the problem of predicting how people will spontaneously divide into groups a set of novel items. This is a process akin to perceptual organization. We therefore employ the simplicity principle from perceptual organization to propose a simplicity model of unconstrained spontaneous grouping. The simplicity model predicts that people would prefer the categories for a set of novel items that provide the simplest encoding of these items. Classification predictions are derived from the model without information either about the number (...) of categories sought or information about the distributional properties of the objects to be classified. These features of the simplicity model distinguish it from other models in unsupervised categorization (where, for example, the number of categories sought is determined via a free parameter), and we discuss how these computational differences are related to differences in modeling objectives. The predictions of the simplicity model are validated in four experiments. We also discuss the significance of simplicity in cognitive modeling more generally. (shrink)

Critics of appraisal theory have difficulty accepting appraisal (with its constructive flavor) as an automatic process, and hence as a potential cause of most emotions. In response, some appraisal theorists have argued that appraisal was never meant as a causal process but as a constituent of emotional experience. Others have argued that appraisal is a causal process, but that it can be either rule-based or associative, and that the associative variant can be automatic. This article first proposes empirically investigating whether (...) rule-based appraisal can also be automatic and then proposes investigating the automatic nature of constructive (instead of rule-based) appraisal because the distinction between rule-based and associative is problematic. Finally, it discusses experiments that support the view that constructive appraisal can be automatic. (shrink)

Intelligent systems are faced with the problem of securing a principled (ideally, veridical) relationship between the world and its internal representation. I propose a unified approach to visual representation, addressing both the needs of superordinate and basic-level categorization and of identification of specific instances of familiar categories. According to the proposed theory, a shape is represented by its similarity to a number of reference shapes, measured in a high-dimensional space of elementary features. This amounts to embedding the stimulus in a (...) low-dimensional proximal shape space. That space turns out to support representation of distal shape similarities which is veridical in the sense of Shepard's (1968) notion of second-order isomorphism (i.e., correspondence between distal and proximal similarities among shapes, rather than between distal shapes and their proximal representations). Furthermore, a general expression for similarity between two stimuli, based on comparisons to reference shapes, can be used to derive models of perceived similarity ranging from continuous, symmetric, and hierarchical, as in the multidimensional scaling models (Shepard, 1980), to discrete and non-hierarchical, as in the general contrast models (Tversky, 1977; Shepard and Arabie, 1979). (shrink)

When a piece of fruit is in a bowl, and the bowl is on a table, we appreciate not only the individual objects and their features, but also the relations containment and support, which abstract away from the particular objects involved. Independent representation of roles (e.g., containers vs. supporters) and “fillers” of those roles (e.g., bowls vs. cups, tables vs. chairs) is a core principle of language and higherlevel reasoning. But does such role-filler independence also arise in automatic visual processing? (...) Here, we show that it does, by exploring a surprising error that such independence can produce. In four experiments, participants saw a stream of images containing different objects arranged in forcedynamic relations — e.g., a phone contained in a basket, a marker resting on a garbage can, or a knife sitting in a cup. Participants had to respond to a single target image (e.g., a phone in a basket) within a stream of distractors presented under time constraints. Surprisingly, even though participants completed this task quickly and accurately, they false-alarmed more often to images matching the target’s relational category than to those that did not — even when those images involved completely different objects. In other words, participants searching for a phone in a basket were more likely to mistakenly respond to a knife in a cup than to a marker on a garbage can. Follow-up experiments ruled out strategic responses and also controlled for various confounding image features. We suggest that visual processing represents relations abstractly, in ways that separate roles from fillers. (shrink)

Cognitive Penetration holds that cognitive states and processes, specifically propositional attitudes (e.g., beliefs), sometimes directly impact features of perceptual experiences (e.g., the coloring of an object). In contrast, more traditional views hold that propositional attitudes do not directly impact perceptual experiences, but rather are only involved in interpreting or judging these experiences. Understandably, Cognitive Penetration is controversial and has been criticized on both theoretical and empirical grounds. I focus on defending it from the latter kind of objection and in doing (...) so, highlight important features of Cognitive Penetration mechanisms and effects. I first sketch promising criteria for Cognitive Penetration and then address widespread Replication and Demonstration worries about purported instances of it. Next, I present one of the most compelling Cognitive Penetration studies and address specific objections against it and others. I demonstrate that each of these objections misunderstands important features of either Cognitive Penetration mechanisms or the specific studies to which they are applied. Ultimately, I conclude that multiple key studies are not undermined by these objections and con- tinue to provide support for Cognitive Penetration. Correcting these misunderstandings bolsters empirical support for Cognitive Penetration and contributes to a better understand- ing of the mechanisms involved in perceptual processing. (shrink)

This paper forges links between early analytic philosophy and the posits of semiotics. I show that there are some striking and potentially quite important, but perhaps unrecognized, connections between three key concepts in Wittgenstein’s middle and later philosophy, namely, complex, rule-following, and language games. This reveals the existence of a conceptual continuity between Wittgenstein’s “early” and “later” philosophy that can be applied to the analysis of the iterability of representation in computer-generated images. Methodologically, this paper clarifies to at least some (...) degree, the nature, progress and promise of an approach to doing philosophy and semiotics from a modally modest perspective that sees in the intellectual products of humanities, and not in unreflective empiricism, the future of scientific development. This hybrid, non-reductionist approach shows, among other things, that semiotic processes are encoded by specific types of complexes in computer-generated images that display iterability in time and space. (shrink)

Humans are poorer at identifying smells and communicating about them, compared to other sensory domains. They also cannot easily organize odor sensations in a general conceptual space, where geometric distance could represent how similar or different all odors are. These two generalities are more or less accepted by psychologists, and they are often seen as connected: If there is no conceptual space for odors, then olfactory identification should indeed be poor. We propose here an important revision to this conclusion: We (...) believe that the claim that there is no odor space is true only if by odor space, one means a conceptual space representing all possible odor sensations, in the paradigmatic sense used for instance for color. However, in a less paradigmatic sense, local conceptual spaces representing a given subset of odors do exist. Thus the absence of a global odor space does not warrant the conclusion that there is no olfactory conceptual map at all. Here we show how a localist account provides a new interpretation of experts and cross‐cultural categorization studies: Rather than being exceptions to the poor olfactory identification and communication usually seen elsewhere, experts and cross‐cultural categorization are here taken to corroborate the existence of local conceptual spaces. (shrink)

Events can be modeled through a geometric approach, representing event structures in terms of spaces and mappings between spaces. At least two spaces are needed to describe an event, an action space and a result space. In this article, we invoke general mathematical structures in order to develop this geometric perspective. We focus on three cognitive processes that are crucially involved in events: causal thinking, control of action and learning by generalization. These cognitive processes are supported by three corresponding mathematical (...) properties: monotonicity (that we relate to qualitative causal thinking and allows extrapolation); continuity (that plays a key role in our activities of action control); and convexity (that facilitates generalization and the categorization of events, and enables interpolation). We define how such properties constrain events representations and relate them to thinking about events. We discuss the relevance of the three constraints for event segmentation and explore the implications of such constraints for semantics. We conclude by a discussion that relates our approach to other accounts of events. (shrink)

The origin of colour categories and their relationship to colour perception have been the prime example for testing the influence of language on perception and thought and more generally for investigating the biological, ecological and cultural determination of human cognition. These themes are central to a broad range of disciplines, including vision research, neuroscience, cognitive psychology, developmental science, cultural anthropology, linguistics, computer science, and philosophy. Unfortunately, though, it has been tacitly taken for granted that the conceptual assumptions and methodological practices (...) from the dawn of empirical research on colour categorisation are the gold standard for current colour category research. Here, we show that these assumptions and practices are obsolete and flawed and have led to four fundamental and widespread misconceptions about colour categorisation: 1.) that colour perception is inherently categorical; 2.) that English Basic Colour Terms correspond to universal categories that are the end point of a fixed evolutionary sequence; 3.) that the prototypes of English basic colour terms are perceptually salient and qualify as focal colours; and 4.) that colour category research essentially revolves around the universalism-realism debate. State-of-the-art research on colour categorisation provides new, more sophisticated approaches and allows for rectifying those four statements. At the same time, some of the questions underlying those statements are not convincingly answered yet and constitute major challenges to future research. The critical considerations on colour categorisation may be transferred to research on other kinds of perceptual categorisation to inspire new, more general research questions. (shrink)

Our ordinary judgments and our metaphysical theories share a common commitment to facts about resemblance. The nature of resemblance is, however, a matter of no small controversy. This essay examines some of the pressing questions that arise regarding the status and structure of resemblance. Among those to be discussed in what follows: what kinds of resemblance relations are there? Can resemblance be analyzed in terms of the sharing of properties? Is resemblance an objective or subjective matter? What, if any, resemblance (...) facts are fundamental? How does resemblance relate to naturalness? (shrink)

Pictures are 2D surfaces designed to elicit 3D-scene-representing experiences from their viewers. In this essay, I argue that philosophers have tended to underestimate the relevance of research in vision science to understanding the nature of pictorial experience. Both the deeply entrenched methodology of virtual psychophysics as well as empirical studies of pictorial space perception provide compelling support for the view that pictorial experience and seeing face-to-face are experiences of the same psychological, explanatory kind. I also show that an empirically informed (...) account of pictorial experience provides resources to develop a novel, resemblance-based account of depiction. According to what I call the deep resemblance theory, pictures work by presenting virtual models of objects and scenes in phenomenally 3D, pictorial space. (shrink)

Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ—that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, (...) “different” responses are faster for low-similarity than for high-similarity pairs. In contrast, identifying a specific difference generally requires a full structural alignment of the two images, and this alignment process is faster for high-similarity pairs. We described four experiments that demonstrate this dissociation and show that the results can be simulated using the Structure-Mapping Engine. These results pose a significant challenge for nonstructural accounts of similarity comparison and suggest that structural alignment processes play a significant role in visual comparison. (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.”.

Evidence from aphasia is considered that leads to a distinction between abstract and concrete thought processes and hence for a distinction between rules and similarity. It is argued that perceptual classification is inherently a rule-following procedure and these rules are unable to be followed when a patient has difficulty with name comprehension and retrieval.

Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural networks have reached or surpassed human accuracy on tasks such as identifying objects in natural images. These networks learn representations of real‐world stimuli that can potentially be leveraged to capture psychological representations. We find that state‐of‐the‐art object classification networks provide surprisingly accurate predictions of human similarity judgments for (...) natural images, but they fail to capture some of the structure represented by people. We show that a simple transformation that corrects these discrepancies can be obtained through convex optimization. We use the resulting representations to predict the difficulty of learning novel categories of natural images. Our results extend the scope of psychological experiments and computational modeling by enabling tractable use of large natural stimulus sets. (shrink)

Events have beginnings, ends, and often overlap in time. A major question is how perceivers come to parse a stream of multimodal information into meaningful units and how different event boundaries may vary event processing. This work investigates the roles of these three types of event boundaries in constructing event temporal relations. Predictions were made based on how people would err according to the beginning state, end state, and overlap heuristic hypotheses. Participants viewed animated events that include all the logical (...) possibilities of event temporal relations, and then made temporal relation judgments. The results showed that people make use of the overlap between events and take into account the ends and beginnings, but they weight ends more than beginnings. Neural network simulations showed a self‐organized distinction when learning temporal relations between events with overlap versus those without. (shrink)

Cognitive Penetration holds that cognitive states and processes, specifically propositional attitudes (e.g., beliefs), sometimes directly impact features of perceptual experiences (e.g., the coloring of an object). In contrast, more traditional views hold that propositional attitudes do not directly impact perceptual experiences, but rather are only involved in interpreting or judging these experiences. Understandably, Cognitive Penetration is controversial and has been criticized on both theoretical and empirical grounds. I focus on defending it from the latter kind of objection and in doing (...) so, highlight important features of Cognitive Penetration mechanisms and effects. I first sketch promising criteria for Cognitive Penetration and then address widespread Replication and Demonstration worries about purported instances of it. Next, I present one of the most compelling Cognitive Penetration studies and address specific objections against it and others. I demonstrate that each of these objections misunderstands important features of either Cognitive Penetration mechanisms or the specific studies to which they are applied. Ultimately, I conclude that multiple key studies are not undermined by these objections and continue to provide support for Cognitive Penetration. Correcting these misunderstandings bolsters empirical support for Cognitive Penetration and contributes to a better understanding of the mechanisms involved in perceptual processing. (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)

A similarity space is a hyperspace in which the dimensions represent various dimensions on which objects may differ. The similarity space theory of concepts is the thesis that concepts are regions of similarity spaces that are somehow realized in the brain. Proponents of such a theory of concepts include Paul Churchland and Peter Gärdenfors. This paper argues that the similarity space theory of concepts is mistaken because regions of similarity spaces cannot serve as the components of judgments. It emerges that (...) although similarity spaces cannot model concepts, they may model a kind of nonconceptual representation. (shrink)

In two eye-tracking studies we investigated the influence of Mandarin numeral classifiers – a grammatical category in the language – on online overt attention. Mandarin speakers were presented with simple sentences through headphones while their eye-movements to objects presented on a computer screen were monitored. The crucial question is what participants look at while listening to a pre-specified target noun. If classifier categories influence Mandarin speakers' general conceptual processing, then on hearing the target noun they should look at objects that (...) are members of the same classifier category – even when the classifier is not explicitly present. The data show that when participants heard a classifier they shifted overt attention significantly more to classifiermatch objects than to distractor objects, but when the classifier was not explicitly presented in speech, overt attention to classifier-match objects and distractor objects did not differ. This suggests that although classifier distinctions do influence eye-gaze behavior, they do so only during linguistic processing of that distinction and not in moment-to-moment general conceptual processing. (shrink)

Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic assumptions about natural kinds, he derived an exponential decay function as the form of the universal generalization gradient, which accords strikingly well with a wide range of empirical data. However, his original formulation applied only to the ideal case of generalization from a single encountered stimulus to a (...) single novel stimulus, and for stimuli that can be represented as points in a continuous metric psychological space. Here we recast Shepard's theory in a more general Bayesian framework and show how this naturally extends his approach to the more realistic situation of generalizing from multiple consequential stimuli with arbitrary representational structure. Our framework also subsumes a version of Tversky's set-theoretic model of similarity, which is conventionally thought of as the primary alternative to Shepard's continuous metric space model of similarity and generalization. This unification allows us not only to draw deep parallels between the set-theoretic and spatial approaches, but also to significantly advance the explanatory power of set-theoretic models. Key Words: additive clustering; Bayesian inference; categorization; concept learning; contrast model; features; generalization; psychological space; similarity. (shrink)

Measuring perceived similarity is an important issue in visual perception of faces, since a measure of the perceived similarity between faces may be used to investigate fundamental tasks like face categorization and recognition. Despite its fundamental role, measuring perceived similarity between faces is not trivial from both a theoretical and methodological point of view. In this paper we present theoretical arguments that undermine the method currently most used to measure perceived similarity between faces in visual perception, and we propose an (...) alternative method. We finally compare the two methods and find some empirical evidence that the proposed method can provide a more reliable evaluation of the perceived similarity between faces. (shrink)

To explain how abstract concepts are grounded in sensory-motor experiences, several theories have been proposed. I will discuss two of these proposals, Conceptual Metaphor Theory and Situated Cognition, and argue why they do not fully explain grounding. A central idea in Conceptual Metaphor Theory is that image schemas ground abstract concepts in concrete experiences. Image schemas might themselves be abstractions, however, and therefore do not solve the grounding problem. Moreover, image schemas are too simple to explain the full richness of (...) abstract concepts. Situated cognition might provide such richness. Research in our laboratory, however, has shown that even for concrete concepts, sensory-motor grounding is task dependent. Therefore, it is questionable whether abstract concepts can be significantly grounded in sensory-motor processing. (shrink)

A growing consensus in the philosophy and psychology of concepts is that while theories such as the prototype, exemplar, and theory theories successfully account for some instances of concept formation and application, none of them successfully accounts for all such instances. I argue against this ‘new consensus’ and show that the problem is, in fact, more severe: the explanatory force of each of these theories is limited even with respect to the phenomena often cited to support it, as each fails (...) to satisfy an important explanatory desideratum with respect to these phenomena. I argue that these explanatory shortcomings arise from a shared assumption on the part of these theories, namely, they take similarity judgements and application of causal knowledge to be discrete elements in a theory of concepts. I further propose that the same assumption carries over into alternative theories offered by proponents of the new consensus: pluralism, eliminativism, and hybrid theories. I put forth a sketch of an integrated model of concept formation and application, which rejects this shared assumption and satisfies the explanatory desiderata I discuss. I suggest that this model undermines the motivation for hybrid, pluralist, and eliminativist accounts of concepts. _1_ Introduction _2_ The Similarity-Based Approach and the Importance of Theory _2.1_ The similarity-based approach _2.2_ The selection desideratum _2.3_ Causal knowledge as satisfying the selection desideratum _3_ The Theory-Based Approach and the Importance of Similarity _3.1_ The theory-based approach _3.2_ The range desideratum _3.3_ Similarity as satisfying the range desideratum _4_ An Integrated Approach to Concepts _4.1_ An integrated model _4.2_ The integrated theory versus hybrid theories of concepts _5_ Conclusion. (shrink)

Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes’ necks get longer over generations, or how ink dropped into water appears to “flow”). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as being (...) caused by controlling agents with intentional goals, as well as express a variety of many other misconceived notions. In this article, we provide a hypothesis for what constitutes a misconceived explanation; why misconceived explanations are so prevalent, robust, and resistant to instruction; and offer one approach of how they may be overcome. In particular, we hypothesize that students misunderstand many science processes because they rely on a generalized version of narrative schemas and scripts (referred to here as a Direct-causal Schema) to interpret them. For science processes that are sequential and stage-like, such as cycles of moon, circulation of blood, stages of mitosis, and photosynthesis, a Direct-causal Schema is adequate for correct understanding. However, for science processes that are non-sequential (or emergent), such as diffusion, natural selection, osmosis, and heat flow, using a Direct Schema to understand these processes will lead to robust misconceptions. Instead, a different type of general schema may be required to interpret non-sequential processes, which we refer to as an Emergent-causal Schema. We propose that students lack this Emergent Schema and teaching it to them may help them learn and understand emergent kinds of science processes such as diffusion. Our study found that directly teaching students this Emergent Schema led to increased learning of the process of diffusion. This article presents a fine-grained characterization of each type of Schema, our instructional intervention, the successes we have achieved, and the lessons we have learned. (shrink)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

“In reality, all arguments from experience are founded on the similarity which we discover among natural objects, and by which we are induced to expect effects similar to those which we have found to follow from such objects. ... From causes which appear similar we expect similar effects.”.