We examine the role of category representations for decision-making in real-life tasks. To this end, we empirically examine how people categorize kitchen objects and make use of categories when storing objects in a kitchen. We then compare two computational models and their ability to represent the participants’ mental models. We discuss the advantages and disadvantages of the models and point the way to further research.

Hume is an experimental philosopher who attempts to understand why we think, feel, and act as we do. But how should we evaluate the adequacy of his proposals? This chapter examines Hume’s account from the perspective of interdisciplinary work in cognitive science.

This paper explores the role of aesthetic judgements in mathematics by focussing on the relationship between the epistemic and aesthetic criteria employed in such judgements, and on the nature of the psychological experiences underpinning them. I claim that aesthetic judgements in mathematics are plausibly understood as expressions of what I will call ‘aesthetic-epistemic feelings’ that serve a genuine cognitive and epistemic function. I will then propose a naturalistic account of these feelings in terms of sub-personal processes of representing and assessing (...) the relation between cognitive processes and certain properties of the stimuli at which they are directed. (shrink)

ABSTRACT This paper explores the role of aesthetic judgements in mathematics by focussing on the relationship between the epistemic and aesthetic criteria employed in such judgements, and on the nature of the psychological experiences underpinning them. I claim that aesthetic judgements in mathematics are plausibly understood as expressions of what I will call ‘aesthetic-epistemic feelings’ that serve a genuine cognitive and epistemic function. I will then propose a naturalistic account of these feelings in terms of sub-personal processes of representing and (...) assessing the relation between cognitive processes and certain properties of the stimuli at which they are directed. (shrink)

I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...) the environment; such knowledge is optimally acquired independently of conscious efforts to learn; and it can be used implicitly to solve problems and make accurate decisions about novel stimulus circumstances. Various epistemological issues and related problems such as intuition, neuroclinical disorders of learning and memory, and the relationship of evolutionary processes to cognitive science are also discussed. (shrink)

Misremembering is a systematic and ordinary occurrence in our daily lives. Since it is commonly assumed that the function of memory is to remember the past, misremembering is typically thought to happen because our memory system malfunctions. In this paper I argue that not all cases of misremembering are due to failures in our memory system. In particular, I argue that many ordinary cases of misremembering should not be seen as instances of memory’s malfunction, but rather as the normal result (...) of a larger cognitive system that performs a different function, and for which remembering is just one operation. Building upon extant psychological and neuroscientific evidence, I offer a picture of memory as an integral part of a larger system that supports not only thinking of what was the case and what potentially could be the case, but also what could have been the case. More precisely, I claim that remembering is a particular operation of a cognitive system that permits the flexible recombination of different components of encoded traces into representations of possible past events that might or might not have occurred, in the service of constructing mental simulations of possible future events. So that imagination and memory are but one thing, which for diverse considerations hath diverse names.Thomas Hobbes, Leviathan 1.2. (shrink)

Are the following propositions true of the colors: No object can be more than one determinable or determinate color all over at the same time (Incompatibility); the colors of objects are mind-independent (Objectivism); and most human observers usually perceive the colors of objects veridically in typical conditions (Veridicality)? One reason to think not is that the empirical literature appears to support the proposition that there is mass perceptual disagreement about the colors of objects amongst human observers in typical conditions (P-Disagreement). (...) In this article, we defend Incompatibility, Objectivism, and Veridicality by calling into question whether the empirical literature really supports P-Disagreement. (shrink)

Beginning in the late 1960s, psychologists began to challenge the view the definitional theory of concepts. According to that theory a concept is a mental representation comprising representations of properties (or “features”) that are individually necessary and jointly sufficient for membership in a category. In place of the definitional view, psychologists initially put forward the prototype theory of concept, according to which concepts comprise representations of features that are typical, salient, and diagnostic for category membership, but not necessarily necessary. The (...) prototype theory gained considerable support in the 1970s, but came under attack in the 1980s. One objection, most forcefully advanced by Jerry Fodor, is that prototypes do not combine compositionally. Compositionality is said to be an adequacy condition on a theory of concepts. If prototypes don’t compose, then prototypes are not concepts. Or so the argument goes. (shrink)

It has been a vexing question in recent years whether concepts are fuzzy. In this paper several views on the fuzziness of concepts are pointed out to have stemmed from dubious concepts of fuzziness. The underlying notions of the roles feasibly played byprototype, set, andprobability in modeling concepts strongly suggest that the controversy originates from a vague relation between intuitive and mathematical ideas in the cognitive sciences. It is argued that the application of fuzzy sets cannot resolve this vagueness since (...) they are one sided,viz., defined on sets. An alternative definition based on classes (in the sense of axiomatic set theory) is proposed. (shrink)

In Book I, Part I, Section VII of the Treatise, Hume sets out to settle, once and for all, the early modern controversy over abstract ideas. In order to do so, he tries to accomplish two tasks: (1) he attempts to defend an exemplar-based theory of general language and thought, and (2) he sets out to refute the rival abstraction-based account. This paper examines the successes and failures of these two projects. I argue that Hume manages to articulate a plausible (...) theory of general ideas; indeed, a version of his account has defenders in contemporary cognitive science. But Hume fails to refute the abstraction-based account, and as a result, the early modern controversy ends in a stalemate, with both sides able to explain how we manage to speak and think in general terms. Although Hume fails to settle the controversy, he nevertheless advances it to a point from which we have yet to progress: the contemporary debate over abstract ideas in cognitive science has stalled on precisely this point. (shrink)

This paper studies the learnability of natural concepts in the context of the conceptual spaces framework. Previous work proposed that natural concepts are represented by the cells of optimally partitioned similarity spaces, where optimality was defined in terms of a number of constraints. Among these is the constraint that optimally partitioned similarity spaces result in easily learnable concepts. While there is evidence that systems of concepts generally regarded as natural satisfy a number of the proposed optimality constraints, the connection between (...) naturalness and learnability has been less well studied. To fill this gap, we conduct a computational study employing two standard models of concept learning. Applying these models to the learning of color concepts, we examine whether natural color concepts are more readily learned than nonnatural ones. Our findings warrant a positive answer to this question for both models employed, thus lending empirical support to the notion that learnability is a distinctive characteristic of natural concepts. (shrink)

What the Sorites has to tell us is a simple truth regarding our categories. It appears to saddle us with something other than a simple truth—something worse, a contradiction or a problem or a paradox—only when we insist on viewing it through a discrete logic of categories. Discrete categories and discrete logic are for robots. We aren’t robots, and the simple truth is that we don’t handle categories in the way any discrete logic would demand. For us non-robots, what the (...) Sorites has to offer is a straightforward truth regarding how incapable robots and their logic are of handling categories like ours. (shrink)

Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference problem, allows for informed inferences about novel feature combinations, and performs robustly across different statistical environments. We designed a new Bayesian classification learning model that incorporates varying degrees of prior belief in class-conditional independence, learns whether or not independence holds, (...) and adapts its behavior accordingly. Theoretical results from two simulation studies demonstrate that classification behavior can appear to start simple, yet adapt effectively to unexpected task structures. Two experiments—designed using optimal experimental design principles—were conducted with human learners. Classification decisions of the majority of participants were best accounted for by a version of the model with very high initial prior belief in class-conditional independence, before adapting to the true environmental structure. Class-conditional independence may be a strong and useful default assumption in category learning tasks. (shrink)

We extend Mangan's account of fringe consciousness by discussing our work on processing experiences. Our research shows that variations in speed at different stages of perceptual processing can jointly contribute to subjective processing ease, supporting Mangan's notion that different mental processes condense into one subjective experience. We also discuss our studies showing that facilitation of perceptual processing leads to positive affect, supporting Mangan's suggestion that an evaluative component is built into cognitive phenomenology. Finally, we review research demonstrating that people draw (...) on processing experiences to make a variety of judgments, supporting Mangan's emphasis on the functional importance of cognitive feelings. (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)

A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, (1) between learning that takes place with versus without concurrent awareness, and (2) between learning that involves the encoding of instances (or fragments) versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning (...) derived from subliminal learning, conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks (e.g., artificial grammar learning) is predominantly based on rule abstraction is questionable. When subjects cannot report the rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning. (shrink)

Understanding novel phrases (e.g. upside‐down daisy) and classifying objects in categories named by phrases ought to have common properties, but you'd never know it from current theories. The best candidate for both jobs is the Theory Theory, but it faces difficulties when theories are impoverished. A potential solution is a dual approach that couples theories (representations‐about categories) with fixed mentalese expressions (representations‐of categories). Both representations combine information in parallel when understanding phrases. Although there are objections to the notion that theories (...) can combine, some of them lose their force when applied to a suitable dual model. (shrink)

Este artículo defiende la relevancia de la filosofía en el estudio contemporáneo de conceptos. Con el desarrollo de la ciencia cognitiva, la teorización naturalista e interdisciplinaria acerca de los conceptos ha cobrado impulso. En este contexto, se ha argumentado recientemente que las teorías filosóficas de conceptos no son acerca del tipo de cosas que interesan a los psicólogos, descartando así la pertinencia científica de la contribución filosófica mencionada. Presentamos y discutimos dos casos que sugieren lo contrario, como un intento de (...) reivindicar el papel crucial que tiene la filosofía en el desarrollo de teorías empíricas de conceptos. (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)

This article proposes a new model of human concept learning that provides a rational analysis of learning feature‐based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space—a concept language of logical rules. This article compares the model predictions to human generalization judgments in several well‐known category learning experiments, and finds good agreement for both average and individual participant generalizations. This article further investigates judgments for a broad set of 7‐feature concepts—a more natural setting in several (...) ways—and again finds that the model explains human performance. (shrink)

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)

An integrated representation of large‐scale space, or cognitive map, colled PLAN, is presented that attempts to address a broader spectrum of issues than has been previously attempted in a single model. Rather than examining way‐finding as a process separate from the rest of cognition, one or the fundamental goals of this work is to examine how the wayfinding process is integrated into general cognition. One result of this approach is that the model is “heads‐up,” or scene‐based, because it takes advantage (...) of the properties of the human visual system and, particularly, the visual system's split into two pathways. The emphasis on the human location or “where” system is new to cognitive mapping and is port of an attempt to synthesize prototype theory, associative networks and location together in a connectionist system. Not all of PLAN is new, however. Many of its parts have analogues in one or another preexisting theory. What makes PLAN unique is integrating the various components into a coherent whole, and the capacity of this resulting system to speak to a wide range of constraints. Our approach emphasizes adaptiveness; thus, our focus on such issues as ease of use and efficiency of learning. The result is a model that has a stronger relationship both to the environment, and to the ways that humans interact with it, compared with previous models. The resulting model is examined in some detail and compared to other systems. (shrink)

Research in education and cognitive development suggests that explaining plays a key role in learning and generalization: When learners provide explanations—even to themselves—they learn more effectively and generalize more readily to novel situations. This paper proposes and tests a subsumptive constraints account of this effect. Motivated by philosophical theories of explanation, this account predicts that explaining guides learners to interpret what they are learning in terms of unifying patterns or regularities, which promotes the discovery of broad generalizations. Three experiments provide (...) evidence for the subsumptive constraints account: prompting participants to explain while learning artificial categories promotes the induction of a broad generalization underlying category membership, relative to describing items (Exp. 1), thinking aloud (Exp. 2), or free study (Exp. 3). Although explaining facilitates discovery, Experiment 1 finds that description is more beneficial for learning item details. Experiment 2 additionally suggests that explaining anomalous observations may play a special role in belief revision. The findings provide insight into explanation’s role in discovery and generalization. (shrink)

Information management systems improve the retention of information in large collections. As such they act as memory prostheses, implying an ideal basis in human memory models. Since humans process information by association, and situate it in the context of space and time, systems should maximize their effectiveness by mimicking these functions. Since human attentional capacity is limited, systems should scaffold cognitive efforts in a comprehensible manner. We propose the Principles of Mnemonic Associative Knowledge (P-MAK), which describes a framework for semantically (...) identifying, organizing, and retrieving information, and for encoding episodic events by time and stimuli. Inspired by prominent human memory models, we propose associative networks as a preferred representation. Networks are ideal for their parsimony, flexibility, and ease of inspection. Networks also possess topological properties—such as clusters, hubs, and the small world—that aid analysis and navigation in an information space. Our cognitive perspective addresses fundamental problems faced by information management systems, in particular the retrieval of related items and the representation of context. We present evidence from neuroscience and memory research in support of this approach, and discuss the implications of systems design within the constraints of P-MAK’s principles, using text documents as an illustrative semantic domain. (shrink)

The term "false memories" has been used to refer to suggestibility experiments in which whole events are apparently confabulated and in media accounts of contested memories of childhood abuse. Since 1992 psychologists have increasingly used the term "false memory" when discussing memory errors for details, such as specific words within word lists. Use of the term to refer to errors in details is a shift in language away from other terms used historically (e.g., "memory intrusions"). We empirically examine this shift (...) in language and discuss implications of the new use of the term "false memories." Use of the term presents serious ethical challenges to the data-interpretation process by encouraging over-generalization and misapplication of research findings on word memory to social issues. (shrink)