One of the main limitations of natural language‐based approaches to meaning is that they do not incorporate multimodal representations the way humans do. In this study, we evaluate how well different kinds of models account for people's representations of both concrete and abstract concepts. The models we compare include unimodal distributional linguistic models as well as multimodal models which combine linguistic with perceptual or affective information. There are two types of linguistic models: those based on text corpora and those derived (...) from word association data. We present two new studies and a reanalysis of a series of previous studies. The studies demonstrate that both visual and affective multimodal models better capture behavior that reflects human representations than unimodal linguistic models. The size of the multimodal advantage depends on the nature of semantic representations involved, and it is especially pronounced for basic‐level concepts that belong to the same superordinate category. Additional visual and affective features improve the accuracy of linguistic models based on text corpora more than those based on word associations; this suggests systematic qualitative differences between what information is encoded in natural language versus what information is reflected in word associations. Altogether, our work presents new evidence that multimodal information is important for capturing both abstract and concrete words and that fully representing word meaning requires more than purely linguistic information. Implications for both embodied and distributional views of semantic representation are discussed. (shrink)

It is widely agreed that generics tolerate exceptions. It turns out, however, that exceptions are tolerated only so long as they do not violate homogeneity: when the exceptions are not concentrated in a salient “chunk” of the domain of the generic. The criterion for salience of a chunk is cognitive: it is dependent on the way in which the domain is mentally represented. Findings of psychological experiments about the ways in which different domains are represented, and the actors affecting such (...) representations, account for judgments of generic sentences, facts which cannot be explained by linguistics alone. The reason for the homogeneity requirement itself is, in turn, also dependent on cognitive considerations. Generics express default rules, and psychological findings have shown that, the more homogeneous the domain, the easier it is for subjects to infer rules about it. Thus, cognitive results form a crucial part of a comprehensive account of the meaning of a linguistic expression. (shrink)

This paper offers a solution to a problem in Herschel studies by drawing on the dynamic frame model for concept representation offered by cognitive psychology. Applying the frame model to represent the conceptual frameworks of the particle and wave theories, this paper shows that discontinuity between the particle and wave frameworks consists mainly in the transition from a particle notion ‘side’ to a wave notion ‘phase difference’. By illustrating intraconceptual relations within concepts, the frame representations reveal the ontological differences between (...) these two concepts. ‘Side’ is an object concept built on spatial relations, but ‘phase difference’ is an event concept built on temporal relations. The conceptual analyses display a possible cognitive source of Herschel’s misconception of polarization. Limited by his experimental works and his philosophical beliefs, Herschel comprehended polarization solely in terms of spatial relations, which prevented him from replacing the object concept ‘side’ with the event concept ‘phase difference’, and eventually resulted in his failure to understand the wave account of polarization.Author Keywords: Herschel; Polarization; Object concept; Event concept; Frame; Cognitive psychology. (shrink)

: This paper offers a preliminary analysis of conceptual change between event concepts. It begins with a brief review of the major findings of cognitive studies on event knowledge. The script model proposed by Schank and Abelson was the first attempt to represent event knowledge. Subsequent cognitive studies indicated that event knowledge is organized in the form of dimensional organizations in which temporally successive actions are related causally. This paper proposes a frame representation to capture and outline the internal structure (...) of event concepts, in particular, their causal connections. The frame representation offers an effective method to analyze the relations between event concepts, and to expose the unique cognitive mechanisms behind conceptual change involved event concepts. Finally this paper shows that the frame representation of event concepts is instrumental to understanding an important historical episode of conceptual change in the context of nineteenth-century optics. (shrink)

Many recent cognitive studies reveal that human cognition is inherently perceptual, sharing systems with perception at both the conceptual and the neural levels. This paper introduces Barsalou's theory of perceptual symbols and explores its implications for philosophy of science. If perceptual symbols lie in the heart of conceptual processing, the process of attribute selection during concept representation, which is critical for defining similarity and thus for comparing taxonomies, can no longer be determined solely by background beliefs. The analogous nature of (...) perceptual symbols and the spatial nature of intraconceptual relations impose new constraints on attribute selection. These constraints help people with different background beliefs select compatible attributes, which constitute a common "platform" for taxonomy comparison. (shrink)

A taxonomy of part‐whole or meronymic relations is developed to explain the ordinary English‐speaker's use of the term “part of” and its cognates. The resulting classification yields six types of meronymic relations: 1. component‐integral object (pedal‐bike), 2. member‐collection (ship‐fleet), 3. portion‐mass (slice‐pie), 4. stuff‐object (steel‐car), 5. feature‐activity (paying‐shopping), and 6. place‐area (Everglades‐Florida). Meronymic relations ore further distinguished from other inclusion relations, such as spatial inclusion, and class inclusion, and from several other semantic relations: attribution, attachment, and ownership. This taxonomy is (...) then used to explain cases of apparent intransitivity in merological syllogisms, and standard form syllogisms whose premises express different inclusion relations. The data suggest that intransitivities arise due to equivocations between different types of semantic relations. These results are then explained by means of the relation element theory which accounts for the character and behavior of semantic relations in terms of more primitive relational elements. The inferential phenomena observed are then explained by means of a single principle of element matching. (shrink)

This review article explores several senses in which it can be held that the (actual, psychological) concept of an object is a formal concept, as opposed, here, to being a sortal concept. Some recent positions both from the philosophical and psychological literature are analyzed: Object-sortalism (Xu), quasi-sortalist reductive strategies (Bloom), qualified sortalism (Wiggins), demonstrative theories (Fodor), and anti-sortalism (Ayers).

Cognitive developmental evidence is sometimes conscripted to support ''naturalized epistemology'' arguments to the effect that a general epistemic stance leads children to build theory-like accounts of underlying properties of kinds. A review of the evidence suggests that what prompts conceptual acquisition is not a general epistemic stance but a series of category-specific intuitive principles that constitute an evolved ''natural metaphysics''. This consists in a system of categories and category-specific inferential processes founded on definite biases in prototype formation. Evidence for this (...) system provides a better understanding of the limited ''plasticity'' of ontological commitments as well as a computationally plausible account of their initial state, avoiding ambiguities about innateness. This may provide a starting point for a ''naturalized epistemology'' that takes into account evolved properties of human conceptual structures. (shrink)

Cognitive developmental evidence is sometimes conscripted to support ''naturalized epistemology'' arguments to the effect that a general epistemic stance leads children to build theory-like accounts of underlying properties of kinds. A review of the evidence suggests that what prompts conceptual acquisition is not a general epistemic stance but a series of category-specific intuitive principles that constitute an evolved ''natural metaphysics''. This consists in a system of categories and category-specific inferential processes founded on definite biases in prototype formation. Evidence for this (...) system provides a better understanding of the limited ''plasticity'' of ontological commitments as well as a computationally plausible account of their initial state, avoiding ambiguities about innateness. This may provide a starting point for a ''naturalized epistemology'' that takes into account evolved properties of human conceptual structures. (shrink)

Although our concepts of “Mama,” “milk,” and “mice” have much in common, the suggestion that they are identical in structure in the mind of the prelinguistic child is mistaken. Even infants think about objects as different from substances and appreciate the distinction between kinds (e.g., mice) and individuals (e.g., Mama). Such cognitive capacities exist in other animals as well, and have important adaptive consequences.

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

Adaptive Planning is an approach to planning in the commonsense domain. An adaptive planner takes advantage of the habitual nature of many of the planning situations for which it plans by bosing its activities on a memory of pre‐stored plans. A critical issue, and the subject of this paper, is the question of flexibility: How does an adaptive planner refit an old plan in order to meet the demands of some new planning situation? An adaptive planner refits prestored plans by (...) constructing an interpretation of the situation in which it is engaged. Key elements in the theory of adaptive planning are its treatment of specific plans and a notion of situation matching. The theory of adaptive planning has been modeled by a computer program called PLEXUS. (shrink)

The current consensus is that most natural categories are not organized around strict definitions (a list of singly necessary and jointly sufficient features) but rather according to a family resemblance (FR) principle: Objects belong to the same category because they are similar to each other and dissimilar to objects in contrast categories. A number of computational models of category construction have been developed to provide an account of how and why people create FR categories (Anderson, 1990; Fisher, 1987). Surprisingly, however, (...) only a few experiments on category construction or free sorting have been run and they suggest that people do not sort examples by the FR principle. We report several new experiments and a two‐stage model for category construction. This model is contrasted with a variety of other models with respect to their ability to account for when FR sorting will and will not occur. The experiments serve to identify one basis for FR sorting and to support the two‐stage model. The distinctive property of the two‐stage model is that it assumes that people impose more structure than the examples support in the first stage and that the second stage adjusts for this difference between preferred and perceived structure. We speculate that people do not simply assimilate probabilistic structures but rather organize them in terms of discrete structures plus noise. (shrink)

Fundamental to spatial knowledge in all species are the representations underlying object recognition, object search, and navigation through space. But what sets humans apart from other species is our ability to express spatial experience through language. This target article explores the language ofobjectsandplaces, asking what geometric properties are preserved in the representations underlying object nouns and spatial prepositions in English. Evidence from these two aspects of language suggests there are significant differences in the geometric richness with which objects and places (...) are encoded. When an object is named (i.e., with count nouns), detailed geometric properties – principally the object's shape (axes, solid and hollow volumes, surfaces, and parts) – are represented. In contrast, when an object plays the role of either “figure” (located object) or “ground” (reference object) in a locational expression, only very coarse geometric object properties are represented, primarily the main axes. In addition, the spatial functions encoded by spatial prepositions tend to be nonmetric and relatively coarse, for example, “containment,” “contact,” “relative distance,” and “relative direction.” These properties are representative of other languages as well. The striking differences in the way language encodes objects versus places lead us to suggest two explanations: First, there is a tendency for languages to level out geometric detail from both object and place representations. Second, a nonlinguistic disparity between the representations of “what” and “where” underlies how language represents objects and places. The language of objects and places converges with and enriches our understanding of corresponding spatial representations. (shrink)

Cognitive categories in the geographic realm appear to manifest certain special features as contrasted with categories for objects at surveyable scales. We have argued that these features reflect specific ontological characteristics of geographic objects. This paper presents hypotheses as to the nature of the features mentioned, reviews previous empirical work on geographic categories, and presents the results of pilot experiments that used English-speaking subjects to test our hypotheses. Our experiments show geographic categories to be similar to their non-geographic counterparts in (...) the ways in which they generate instances of different relative frequencies at different levels. Other tests, however, provide preliminary evidence for the existence of important differences in subjects’ categorizations of geographic and non-geographic objects, and suggest further experimental work especially with regard to the role in cognitive categorization of different types of object-boundaries at different scales. (shrink)

The frame model, originating in artificial intelligence and cognitive psychology, has recently been applied to change-phenomena traditionally studied within history and philosophy of science. Its application purpose is to account for episodes of conceptual dynamics in the empirical sciences suggestive of incommensurability as evidenced by “ruptures” in the symbolic forms of historically successive empirical theories with similar classes of applications. This article reviews the frame model and traces its development from the feature list model. Drawing on extant literature, examples of (...) frame-reconstructed taxonomic change are presented. This occurs for purposes of comparison with an alternative tool, conceptual spaces. The main claim is that conceptual spaces save the merits of the frame model and provide a powerful model for conceptual change in scientific knowledge, since distinctions arising in measurement theory are native to the model. It is suggested how incommensurability as incomparability of theoretical frameworks might be avoided. Moreover, as nontranslatability of worldviews, it need not to be treated as a genuine problem of conceptual representation. The status of laws vis à vis their dimensional bases as well as diachronic similarity measures are discussed. (shrink)

A taxonomy of part‐whole or meronymic relations is developed to explain the ordinary English‐speaker's use of the term “part of” and its cognates. The resulting classification yields six types of meronymic relations: 1. component‐integral object (pedal‐bike), 2. member‐collection (ship‐fleet), 3. portion‐mass (slice‐pie), 4. stuff‐object (steel‐car), 5. feature‐activity (paying‐shopping), and 6. place‐area (Everglades‐Florida). Meronymic relations ore further distinguished from other inclusion relations, such as spatial inclusion, and class inclusion, and from several other semantic relations: attribution, attachment, and ownership. This taxonomy is (...) then used to explain cases of apparent intransitivity in merological syllogisms, and standard form syllogisms whose premises express different inclusion relations. The data suggest that intransitivities arise due to equivocations between different types of semantic relations. These results are then explained by means of the relation element theory which accounts for the character and behavior of semantic relations in terms of more primitive relational elements. The inferential phenomena observed are then explained by means of a single principle of element matching. (shrink)

People mentally represent the shapes of objects. For instance, the mental representation of an eagle is different when one thinks about a flying or resting eagle. This study examined the role of shape in mental representations of similes (i.e., metaphoric comparisons). We tested the prediction that when people process a simile they will mentally represent the entities of the comparison as having a similar shape. We conducted two experiments in which participants read sentences that either did (experimental sentences) or did (...) not (control sentences) invite comparing two entities. For the experimental sentences, the ground of the comparison was explicit in Experiment 1 (“X has the ability to Z, just like Y”) and implicit in Experiment 2 (“X is like Y”). After having read the sentence, participants were presented with line drawings of the two objects, which were either similarly or dissimilarly shaped. They judged whether both objects were mentioned in the preceding sentence. For the experimental sentences, recognition latencies were shorter for similarly shaped objects than for dissimilarly shaped objects. For the control sentences, we did not find such an effect of similarity in shape. These findings suggest that a perceptual symbol of shape is activated when processing similes. (shrink)

Glenberg's account falls short in several respects. Besides requiring clearer explication of basic concepts, his account fails to recognize the autonomous nature of perception. His account of what is remembered, and its description, is too static. His strictures against connectionist modeling might be overcome by combining the notions of psychological space and principled learning in an embodied and situated network.

People mentally represent the shapes of objects. For instance, the mental representation of an eagle is different when one thinks about a flying or resting eagle. This study examined the role of shape in mental representations of similes (i.e., metaphoric comparisons). We tested the prediction that when people process a simile they will mentally represent the entities of the comparison as having a similar shape. We conducted two experiments in which participants read sentences that either did (experimental sentences) or did (...) not (control sentences) invite comparing two entities. For the experimental sentences, the ground of the comparison was explicit in Experiment 1 (“X has the ability to Z, just like Y”) and implicit in Experiment 2 (“X is like Y”). After having read the sentence, participants were presented with line drawings of the two objects, which were either similarly or dissimilarly shaped. They judged whether both objects were mentioned in the preceding sentence. For the experimental sentences, recognition latencies were shorter for similarly shaped objects than for dissimilarly shaped objects. For the control sentences, we did not find such an effect of similarity in shape. These findings suggest that a perceptual symbol of shape is activated when processing similes. (shrink)

Our earliest tools are our bodies. Our hands raise and turn and toss and carry and push and pull, our legs walk and climb and kick allowing us to move and act in the world and to create the multitude of artifacts that improve our lives. The list of actions made by our hands and feet and other parts of our bodies is long. What is more remarkable is we turn those actions in the world into actions on thought through (...) gestures, language, and graphics, thereby creating cognitive tools that expand the mind. The focus here is gesture; gestures transform actions on perceptible objects to actions on imagined thoughts, carrying meaning with them rapidly, precisely, and directly. We review evidence showing that gestures enhance our own thinking and change the thought of others. We illustrate the power of gestures in studies showing that gestures uniquely change conceptions of time, from sequential to simultaneous, from sequential to cyclical, and from a perspective embedded in a timeline to an external perspective looking on a timeline, and by so doing obviate the ambiguities of an embedded perspective. We draw parallels between representations in gesture and in graphics; both use marks or actions arrayed in space to communicate more immediately than symbolic language. (shrink)

This paper reports the first empirical investigation of the hypothesis that epistemic appraisals form part of the structure of concepts. To date, studies of concepts have focused on the way concepts encode properties of objects and the way those features are used in categorization and in other cognitive tasks. Philosophical considerations show the importance of also considering how a thinker assesses the epistemic value of beliefs and other cognitive resources and, in particular, concepts. We demonstrate that there are multiple, reliably (...) judged, dimensions of epistemic appraisal of concepts. Four of these dimensions are accounted for by a common underlying factor capturing how well people believe they understand a concept. Further studies show how dimensions of concept appraisal relate to other aspects of concepts. First, they relate directly to the hierarchical organization of concepts, reflecting the increase in specificity from superordinate to basic and subordinate levels. Second, they predict inductive choices in category-based induction. Our results suggest that epistemic appraisals of concepts form a psychologically important yet previously overlooked aspect of the structure of concepts. These findings will be important in understanding why individuals sometimes abandon and replace certain concepts; why social groups do so, for example, during a “scientific revolution”; and how we can facilitate such changes when we engage in deliberate “conceptual engineering” for epistemic, social, and political purposes. (shrink)

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation (...) and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction. Key Words: concept learning; conceptual development; features; perceptual learning; stimulus encoding. (shrink)

We think of the world around us as divided into physical objects like toasters and daisies, rather than solely as a smear of properties like yellow and smooth. How do we single out these objects? One theory of object concepts uses part‐of relations and relations of connectedness. According to this proposal, an object is a connected spatial item of maximal extent: Any other connected item that overlaps (i.e., shares a part with) the object must be a part of that object. (...) This article reports four experiments that test this proposal. Participants see descriptions or diagrams of spatial items that vary across trials in their relative positions. In separate experiments, participants decide whether the items are physical objects, whether they are wholes, or how many objects are present. All experiments find support for connectedness as a contributor to object status, but they find little support for maximality. The results suggest that maximality is not a necessary feature of wholes or of objects. (shrink)

We re-evaluate existing data that demonstrate a large amount of variability in the content of categories considering the fact that these data have been obtained in a specific task: the production of features of single isolated categories. We present new data that reveal a large consensus when participants have to judge whether or not a given feature is characteristic of a category and we show that classification tasks produce an intermediate level of consensus. We argue that the differences observed between (...) tasks are due to the extent of implied context and we propose a reinterpretation of typicality effects, demonstrating that they are compatible with the existence of a stable conceptual core. In order to explain how the existence of a conceptual core is consistent with variability due to context, we present a theory of categorisation based on a property tree organisation. Within a domain of description, we distinguish between semantic implications (flying → moving) and empirical implications (flying → having wings) as well as between properties used to describe objects. Semantic implications serve to build property lines and Galois lattices are used to reveal category structures according to empirical implications. We show that variability in the category content may be explained by the fact that some properties are emphasised while others are masked according to the context. (shrink)