Although cognitive scientists have learned a lot about concepts, their findings have yet to be organized in a coherent theoretical framework. In addition, after twenty years of controversy, there is little sign that philosophers and psychologists are converging toward an agreement about the very nature of concepts.Doing without Concepts(Machery 2009) attempts to remedy this state of affairs. In this article, I review the main points and arguments developed at greater length inDoing without Concepts.

In questo contributo descriviamo un sistema di creatività computazionale in grado di generare automaticamente nuovi concetti utilizzando una logica descrittiva non monotòna che integra tre ingredienti principali: una logica descrittiva della tipicalità, una estensione probabilistica basata sulla semantica distribuita nota come DISPONTE, e una euristica di ispirazione cognitiva per la combinazione di più concetti. Una delle applicazioni principali del sistema riguarda il campo della creatività computazionale e, più specificatamente, il suo utilizzo come sistema di supporto alla creatività in ambito mediale. (...) In particolare, tale sistema è in grado di: generare nuove storie (a partire da una rappresentazione narrativa di storie pre-esistenti), generare nuovi personaggi (ad es. il nuovo “cattivo” di una serie tv o di un cartone animato) e, in generale, può essere utilizzato per proporre nuove soluzioni e format narrativi da esplorare nell’ambito dell’industria creativa. (shrink)

According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

Traditionally, theories of concepts in psychology assume that concepts are a single, uniform kind of mental representation. But no single kind of representation can explain all of the empirical data for which concepts are responsible. I argue that the assumption that concepts are uniformly the same kind of mental structure is responsible for these theories’ shortcomings, and outline a pluralist theory of concepts that rejects this assumption. On pluralism, concepts should be thought of as being constituted by multiple representational kinds, (...) with the particular kind of concept used on an occasion being determined by the context. I argue that endorsing pluralism does not lead to eliminativism about concepts as an object of scientific interest. (shrink)

We motivate the possibility of using notions and methods derived from quantum physics, and more specifically from the research field known as ‘quantum cognition’, to optimally model different situations in the field of medicine, its decision-making processes and ensuing practices, particularly in relation to chronic and rare diseases. This also as a way to devise alternative approaches to the generally adopted double-blind gold standard.

In this paper I evaluate the soundness of the prototype paradigm, in particular its basic assumption that there are pan-human psychological essences or core meanings that refer to basic-level natural kinds, explaining why, on the whole, human communication and learning are successful. Instead I argue that there are no particular pan-human basic elements for thought, meaning and cognition, neither prototypes, nor otherwise. To illuminate my view I draw on examples from anthropology. More generally I argue that the prototype paradigm exemplifies (...) two assumptions that dominate cognitive science: (1) If human beings use words they mean something particular and what they mean can be discovered by scientific methods. (2) There is a fixed number of domains of categorization, each made up of a fixed number of basic categories. I suggest that these two assumptions lead to Brave New World. (shrink)

The Twin Earth thought experiment invites us to consider a liquid that has all of the superficial properties associated with water (clear, potable, etc.) but has entirely different deeper causal properties (composed of “XYZ” rather than of H2O). Although this thought experiment was originally introduced to illuminate questions in the theory of reference, it has also played a crucial role in empirically informed debates within the philosophy of psychology about people’s ordinary natural kind concepts. Those debates have sought to accommodate (...) an apparent fact about ordinary people’s judgments: Intuitively, the Twin Earth liquid is not water. We present results from four experiments showing that people do not, in fact, have this intuition. Instead, people tend to have the intuition that there is a sense in which the liquid is not water but also a sense in which it is water. We explore the implications of this finding for debates about theories of natural kind concepts, arguing that it supports views positing two distinct criteria for membership in natural kind categories – one based on deeper causal properties, the other based on superficial, observable properties. (shrink)

Semantic composition in language must be closely related to semantic composition in thought. But the way the two processes are explained differs considerably. Focusing primarily on propositional content, language theorists generally take semantic composition to be a truth‐conditional process. Focusing more on extensional content, cognitive theorists take it to be a form of concept combination. But though deep, this disconnect is not irreconcilable. Both areas of theory assume that extensional (i.e., denotational) meanings must play a role. As this article demonstrates, (...) they also have the potential to fulfill a mediative function. What is shown is that extensional meanings are themselves inherently compositional. On this basis, it becomes possible to model semantic composition without assuming the existence of any specifically linguistic/conceptual apparatus. Examples are presented to demonstrate this direct style of modeling. Abstract connections between composition in thought and language can then be made, raising the prospect of a more unified, theoretical account of semantic composition. (shrink)

Some philosophers argue that all concepts cannot have the same representational structure, because no single kind of representation has been successful in accounting for the phenomena related to the formation and application of concepts. Here, I argue against this “appeal to cognitive science” by demonstrating that different theories of the kind concept cohere with different interpretations of the argument. To circumvent the threat of relativism, I argue that theories of concept should be understood as working hypotheses, which are provisionally accepted (...) to facilitate the investigation and explanation of the mind/brain. From this perspective, theories of concept are to be evaluated as part of a comparative analysis of the different kinds of cognitive science they inspire. (shrink)

The principle of compositionality claims that the content of a complex concept is determined by its constituent concepts and the way in which they are composed. However, for prototype concepts this principle is often too rigid. Blurring the division between conceptual composition and belief update has therefore been suggested. Inspired by this idea, we develop a normative account of how belief revision and meaning composition should interact in modifications such as “red apple” or “pet hamster”. We do this by combining (...) the well-known selective modification model :485–527 1988) with the rules of Bayesian belief update. Moreover, we relate this model to systems of defeasible reasoning as discussed in the field of artificial intelligence. (shrink)

From Fine and Kamp in the 70’s—through Osherson and Smith in the 80’s, Williamson, Kamp and Partee in the 90’s and Keefe in the 00’s—up to Sauerland in the present decade, the objection continues to be run that fuzzy logic based theories of vagueness are incompatible with ordinary usage of compound propositions in the presence of borderline cases. These arguments against fuzzy theories have been rebutted several times but evidently not put to rest. I attempt to do so in this (...) paper. (shrink)

Different formal tools are useful for different purposes. For example, when it comes to modelling degrees of belief, probability theory is a better tool than classical logic; when it comes to modelling the truth of mathematical claims, classical logic is a better tool than probability theory. In this paper I focus on a widely used formal tool and argue that it does not provide a good model of a phenomenon of which many think it does provide a good model: I (...) shall argue that while supervaluationism may provide a model of probability of truth, or of assertability, it cannot provide a good model of truth -- supertruth cannot be truth. The core of the argument is that an adequate model of truth must render certain connectives truth-functional (at least in certain circumstances) -- and supervaluationism does not do so (in those circumstances). (shrink)

Abstract A survey of different senses of the term ?representation? is presented. The presentation is guided by the appraisal that this key term is employed in the cognitive literature in different senses and that the distinction between these is not always explicitly stated or appreciated. Furthermore, the different senses seem to be associated with different rationales for the postulation of representation. Given that there may be a lack of convergence between the various senses of the construct in question and the (...) rationales for its postulation, a clear differentiation of these may be crucial for any evaluation of the role of representations in cognition and in cognitive theory. (shrink)

The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial (...) roles of other cognitive processes (such as explanation and credit assignment) are ignored or oversimplified. Learning necessarily involves pragmatic considerations that can only be handled by complex cognitive processes.We provide an alternative framework for learning according to which category definitions must be based on category function. The learning system invokes other cognitive processes to accomplish difficult tasks, makes inferences, analyses and decides among potential features, and specifies how and when categories are to be generated and modified. We also examine the methodological underpinnings of the two approaches and compare their motivations. (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)

In contrast to earlier views that argued for a particular kind of concept, several recent accounts have proposed that there are multiple distinct kinds of concepts, or that there is a plurality of concepts for each category. In this paper, I argue for a novel account of concepts as pluralistic hybrids. According to this view, concepts are pluralistic because there are several concepts for the same category whose use is heavily determined by context. In addition, concepts are hybrids because they (...) typically link together several different kinds of information that are used in the same cognitive processes. This alternative view accounts for the available empirical data, allows for greater cognitive flexibility than Machery's recent account, and overcomes several objections to traditional hybrid views. (shrink)

We investigate the hypothesis that our conceptual systems provide two formally distinct ways of representing categories by investigating the manner in which lexical nominals (e.g., tree, picnic table) and phrasal nominals (e.g., black bird, birds that like rice) are interpreted. Four experiments found that lexical nominals may be mapped onto kind representations, whereas phrasal nominals map onto class representations but not kind representations. Experiment 1 found that phrasal nominals, unlike lexical nominals, are mapped onto categories whose members need not be (...) of a single kind. Experiments 2 and 3 found that categories named by lexical nominals enter into both class inclusion and kind hierarchies and thus support both class inclusion (is a) and kind specification (kind of) relations, whereas phrasal nominals map onto class representations which support only class inclusion relations. Experiment 4 showed that the two types of nominals represent hierarchical relations in different ways. Phrasal nominals (e.g., white bear) are mapped onto classes that have criteria of membership in addition to those specified by the class picked out by the head noun of the phrase (e.g., bear). In contrast, lexical nominals (e.g., polar bear) specify one way to meet the criteria specified by the more general kind concept (e.g., bear). Implications for the language–conceptual system interface, representation of hierarchical relations, lexicalization, and theories of conceptual combination are discussed. (shrink)

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the (...) fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality. (shrink)

Copredication is the phenomenon whereby two or more predicates seem to require that their argument denotes different things. The denotation of words that copredicate has been broadly discussed. In this paper, I investigate the metaphysics behind this question. Thus, mereological theories of dot objects claim that these nouns denote complex entities; Asher (Lexical meaning in context, Cambridge University Press, 2011, https://doi.org/10.1017/CBO9780511793936) thinks that they denote bare particulars; and the Activation Package Theory contends that they stand for multiple denotations. According to (...) the Activation Package Theory, copredicative nouns stand for complex knowledge structures that offer a range of multiple potential denotations. In this paper, I claim that the Activation Package Theory contributes to solve some of the metaphysical questions that arise from copredication. (shrink)

We seem to learn and use concepts in a variety of heterogenous “formats”, including exemplars, prototypes, and theories. Different strategies have been proposed to account for this diversity. Hybridists consider instances in different formats to be instances of a single concept. Pluralists think that each instance in a different format is a different concept. Eliminativists deny that the different instances in different formats pertain to a scientifically fruitful kind and recommend eliminating the notion of a “concept” entirely. In recent years, (...) hybridism has received the most attention and support. However, we are still lacking a cognitive-computational model for concept representation and processing that would underpin hybridism. The aim of this paper is to advance the understanding of concepts by grounding hybridism in a neuroscientific model within the Predictive Processing framework. In the suggested view, the different formats are not distinct parts of a concept but arise from different ways of processing a functionally unified representational structure. (shrink)

The systematicity argument only challenges connectionism if systematicity is a general property of cognition. I examine this thesis in terms of properties of concepts. First, I propose that Evans's Generality Constraint only applies to attributions of belief. Then I defend a variety of conceptual pluralism, arguing that concepts share two fundamental properties related to centrality and belief-attribution, and contending that there are two kinds of concepts that differ in their compositional properties. Finally, I rely on Dual Systems Theory and on (...) differences between animal and human cognition to suggest a scenario of two processing systems that work on different kinds of concepts, with only one of them supporting full systematicity. I sketch a non-classical systematicity argument that rules out classicism as the basis of one of those systems given that it would wrongly entail that both systems are fully systematic. (shrink)

In this paper, I develop a novel account of concept acquisition for an atomistic theory of concepts. Conceptual atomism is rarely explored in cognitive science because of the feeling that atomistic treatments of concepts are inherently nativistic. My model illustrates, on the contrary, that atomism does not preclude the learning of a concept.

A standard view within psychology is that there have been two important shifts in the study of concepts and that each has led to some improvements. The first shift was from the classical theory of concepts to probabilistic theories, including the prototype theory. The second shift was from probabilistic theories to theory-based theories. In this article, I critically evaluate the view that the first shift was a major advance and argue that the prototype theory suffers some of the same problems (...) that have been thought to challenge the classical theory. (shrink)

Machery (2009) has proposed that the notion of ‘concept’ ought to be eliminated from the theoretical vocabulary of psychology. I raise three questions about his argument: (1) Is there a meaningful distinction between concepts and background knowledge? (2) Do we need to discard the hybrid view? (3) Are there really categories of things in the world that are the basis for concepts? Although I argue that the answer to all three is ‘no’, I agree with Machery's conclusion that seeking a (...) single characterization of concepts will not be fruitful for understanding cognitive representations and processes. (shrink)