Many debates in philosophy focus on whether folk or scientific psychological notions pick out cognitive natural kinds. Examples include memory, emotions and concepts. A potentially interesting type of kind is: kinds of mental representations (as opposed, for example, to kinds of psychological faculties). In this chapter we outline a proposal for a theory of representational kinds in cognitive science. We argue that the explanatory role of representational kinds in scientific theories, in conjunction with a mainstream approach to explanation in cognitive (...) science, suggest that representational kinds are multi-level. This is to say that representational kinds’ properties cluster at different levels of explanation and allow for intra- and inter-level projections. (shrink)

The target article focuses on evidence from nonlinguistic faculties to defend the claim that cognition generally traffics in language-of-thought (LoT)-type representations. This focus creates needed space to discuss the mounting accumulation of nonclassical evidence for LoT, but it also misses relevant work in linguistics that directly offers a perspective on specific hypotheses about candidate LoT representations.

This paper exploits recent work on the normative and constitutive roles of knowledge in practical rationality, to put pressure on the idea that speakers could communicate without exploiting linguistic knowledge. I defend cognitivism about meaning, the view that speakers have rationally accessible (i.e., implicit rather than tacit) knowledge of semantic facts and principles, and that this knowledge is constitutive of their linguistic competence.

In evolutionary biology, a trait is said to be optimal if it maximizes the fitness of the organism, that is, if the trait allows the organism to survive and reproduce better than any other competing trait would. In engineering, a design is said to be optimal if it complies with its functional requirements as well as possible. Cognitive science is both a biological and engineering discipline and hence it uses both notions of optimality. Unfortunately, the lack of a clear methodological (...) stance on this tissue has made it common for researchers to conflate these two kinds of optimality. In this paper, I argue that a strict distinction must kept in order to avoid inaccurate assumptions. (shrink)

Je soutiens qu’accepter les explications réalistes intentionnelles du comportement cognitif conduit inévitablement à endosser l’hypothèse du langage de la pensée, et que cette position théorique est, par conséquent, largement répandue chez les philosophes de l’esprit. Au cours de la discussion, je propose un exposé succinct et précis de cette hypothèse et j’analyse une série d’exemples représentatifs de l’argumentation pro-LOT. Après avoir examiné deux cas de résistance à ce type de raisonnement, je conclus en montrant que le soutien accordé à la (...) LOT est empiriquement substantiel, en dépit de la flexibilité et du caractère incomplet de cette hypothèse. (shrink)

Marr’s celebrated contribution to cognitive science (Marr 1982, chap. 1) was the introduction of (at least) three levels of description/explanation. However, most contemporary research has relegated the distinction between levels to a rather dispensable remark. Ignoring such an important contribution comes at a price, or so we shall argue. In the present paper, first we review Marr’s main points and motivations regarding levels of explanation. Second, we examine two cases in which the distinction between levels has been neglected when considering (...) the structure of mental representations: Cummins et al.’s distinction between structural representation and encodings (Cummins in Journal of Philosophy, 93(12):591–614, 1996; Cummins et al. in Journal of Philosophical Research, 30:405–408, 2001) and Fodor’s account of iconic representation (Fodor 2008). These two cases illustrate the kind of problems in which researchers can find themselves if they overlook distinctions between levels and how easily these problems can be solved when levels are carefully examined. The analysis of these cases allows us to conclude that researchers in the cognitive sciences are well advised to avoid risks of confusion by respecting Marr’s old lesson. (shrink)

Epistemology of language, a branch of both epistemology and the philosophy of language, asks what knowledge of language consists in. In this paper, I argue that such an inquiry is a pointless enterprise due to its being based upon the incorrect assumption that linguistic competence requires knowledge of language. However, I do not think the phenomenon of knowledge of language is trivial. I propose a virtue-theoretic account of linguistic competence, and then explain the phenomenon from a virtue-semantic point of view.

Knowledge of a language is a kind of knowledge, the possession of which enables a speaker to understand and perform a variety of linguistic actions in that language. In this paper, I pursue an agency-oriented approach to knowledge of language. I begin by examining two major agency-oriented models of knowledge of language: Michael Dummett's Implicit Knowledge Model and Jennifer Hornsby's Practical Knowledge Model. I argue that each of these models is inadequate for different reasons. I present an Acquaintance Knowledge Model, (...) in which a speaker's knowledge of a language is a combination of the speaker's first-order linguistic ability and second-order acquaintance with his ability and actions. (shrink)

According to the theory theory of folk psychology, our engagement in the folk psychological practices of prediction, interpretation and explanation draws on a rich body of knowledge about psychological matters. According to the simulation theory, in apparent contrast, a fundamental role is played by our ability to identify with another person in imagination and to replicate or re-enact aspects of the other person’s mental life. But amongst theory theorists, and amongst simulation theorists, there are significant differences of approach.

The semantic automata framework, developed originally in the 1980s, provides computational interpretations of generalized quantifiers. While recent experimental results have associated structural features of these automata with neuroanatomical demands in processing sentences with quantifiers, the theoretical framework has remained largely unexplored. In this paper, after presenting some classic results on semantic automata in a modern style, we present the first application of semantic automata to polyadic quantification, exhibiting automata for iterated quantifiers. We also discuss the role of semantic automata in (...) linguistic theory and offer new empirical predictions for sentence processing with embedded quantifiers. (shrink)

The semantic automata framework, developed originally in the 1980s, provides computational interpretations of generalized quantifiers. While recent experimental results have associated structural features of these automata with neuroanatomical demands in processing sentences with quantifiers, the theoretical framework has remained largely unexplored. In this paper, after presenting some classic results on semantic automata in a modern style, we present the first application of semantic automata to polyadic quantification, exhibiting automata for iterated quantifiers. We also discuss the role of semantic automata in (...) linguistic theory and offer new empirical predictions for sentence processing with embedded quantifiers. (shrink)

Abstract In the first part of this essay (Russell, 1988a) I argued that ?cognisance? (roughly: a subject's knowledge of his relation to the physical world as an experiencer of it) cannot be explained in terms of a syntactic theory of mind, due to the ?referential? and ?holistic? nature of this knowledge. The syntactic account of the higher mental functions is immediately intelligible to us due to its derivation from computer technology, so this would not appear to be a happy result (...) for scientific psychology. In this paper I outline a strategy for developing a scientific psychology of cognisance, beginning from the assumption that such a theory should have a similar status to Chomsky's competence theory of human grammar, whilst diverging from Chomsky on the question of how such a theory should be answerable to data. Most of the paper is taken up with illustrating the way in which Jean Piaget's theory of mental development in humans is at least a first approximation to such a theory. (shrink)

ABSTRACTThe seminal work of David Marr, popularized in his classic work Vision, continues to exert a major influence on both cognitive science and philosophy. The interpretation of his work also co...

I defend the non-cognitivist outlook on knowledge of grammar from the criticisms levelled against it by Jonathan Knowles. The first part of the paper is largely critical. First, I argue that Knowles's argument against Christopher Peacocke and Martin Davies's non-cognitivist account of the psychological reality of grammar fails, and thus that no reason has been given to think that cognitivism is integral to an understanding of Chomskyan theoretical linguistics. Second, I argue that cognitivism is philosophically problematic. In particular, I argue (...) (a) that Knowles misunderstands Stephen Stich and Gareth Evans's points about inferential integration; and (b) that Knowles misunderstands the philosophical status and demands of Evans's Generality Constraint. In the final, non-critical part of the paper, I try to show that the Stich and Evans's constraints, together with a Self-Knowledge Constraint, are genuine constitutive constraints by showing how they have rationality as their underlying organizing principle. I argue further that recognizing the constitutive character of these constraints allows one to distinguish two kinds of psychological explanation; in this sense, the constraints mark a genuine boundary in our theorizing about the mind. (shrink)

The meaning of 'most' can be described in many ways. We offer a framework for distinguishing semantic descriptions, interpreted as psychological hypotheses that go beyond claims about sentential truth conditions, and an experiment that tells against an attractive idea: 'most' is understood in terms of one-to-one correspondence. Adults evaluated 'Most of the dots are yellow', as true or false, on many trials in which yellow dots and blue dots were displayed for 200 ms. Displays manipulated the ease of using a (...) 'one-to-one with remainder' strategy, and a strategy of using the Approximate Number System to compare of (approximations of) cardinalities. Interpreting such data requires care in thinking about how meaning is related to verification. But the results suggest that 'most' is understood in terms of cardinality comparison, even when counting is impossible. (shrink)

Davidson conjectured that suitably formulated Tarski-style theories of truth can “do duty” as theories of meaning for the spoken languages that humans naturally acquire. But this conjecture faces a pair of old objections that are, in my view, fatal when combined. Foster noted that given any theory of the sort Davidson envisioned, for a language L, there will be many equally true theories whose theorems pair endlessly many sentences of L with very different specifications of whether or not those sentences (...) are true. And if L includes words ‘true’, then for reasons stressed by Tarski, it’s hard to see how any truth theory for L could be correct. Moreover, each of these concerns amplifies the other. Appealing to possible worlds will not help with Foster’s Problem, for reasons that Chomsky discussed in the 1950s, and appealing to trivalent models of truth will not avoid concerns illustrated with Liar Sentences. (shrink)

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...) make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

Many philosophers suppose that sometimes we think we are saying or thinking something meaningful when in fact we’re not saying or thinking anything at all: we are producing nonsense. But what is nonsense? An account of nonsense must, I argue, meet two constraints. The first constraint requires that nonsense can be rationally engaged with, not just mentioned. In particular, we can reason with nonsense and use it within that-clauses. An account which fails to meet this constraint cannot explain why nonsense (...) appears meaningful. The second constraint requires that nonsense does not express thoughts. An account which fails to meet this constraint undercuts the critical force of the concept of nonsense. I offer an account which meets both constraints. The central idea is that to be under the illusion that some nonsense makes sense is to enter a pretence that the nonsense is meaningful. (shrink)

The debate between the defenders of explanatory unification and explanatory pluralism has been ongoing from the beginning of cognitive science and is one of the central themes of its philosophy. Does cognitive science need a grand unifying theory? Should explanatory pluralism be embraced instead? Or maybe local integrative efforts are needed? What are the advantages of explanatory unification as compared to the benefits of explanatory pluralism? These questions, among others, are addressed in this Synthese’s special issue. In the introductory paper, (...) we discuss the background of the questions, distinguishing integrative theorizing from building unified theories. On the one hand, integrative efforts involve collaboration between various disciplines, fields, approaches, or theories. These efforts could even be quite temporary, without establishing any long-term institutionalized fields or disciplines, but could also contribute to developing new interfield theories. On the other hand, unification can rely on developing complete theories of mechanisms and representations underlying all cognition, as Newell’s “unified theories of cognition”, or may appeal to grand principles, as predictive coding. Here, we also show that unification in contemporary cognitive science goes beyond reductive unity, and may involve various forms of joint efforts and division of explanatory labor. This conclusion is one of the themes present in the content of contributions constituting the special issue. (shrink)

This paper proposes an Interface Transparency Thesis concerning how linguistic meanings are related to the cognitive systems that are used to evaluate sentences for truth/falsity: a declarative sentence S is semantically associated with a canonical procedure for determining whether S is true; while this procedure need not be used as a verification strategy, competent speakers are biased towards strategies that directly reflect canonical specifications of truth conditions. Evidence in favor of this hypothesis comes from a psycholinguistic experiment examining adult judgments (...) concerning ‘Most of the dots are blue’. This sentence is true if and only if the number of blue dots exceeds the number of nonblue dots. But this leaves unsettled, e.g., how the second cardinality is specified for purposes of understanding and/or verification: via the nonblue things, given a restriction to the dots, as in ‘|{x: Dot(x) & ~Blue(x)}|’; via the blue things, given the same restriction, and subtraction from the number of dots, as in ‘|{x: Dot(x)}| – |{x: Dot(x) & Blue(x)}|’; or in some other way. Psycholinguistic evidence and psychophysical modeling support the second hypothesis. (shrink)

Noam Chomsky claims that we know the grammatical principles of our languages in pretty much the same sense that we know ordinary things about the world (e.g. facts), a view about linguistic knowledge that I term ''cognitivism''. In much recent philosophy of linguistics (including that sympathetic to Chomsky's general approach to language), cognitivism has been rejected in favour of an account of grammatical competence as some or other form of mental mechanism, describable at various levels of abstraction (''non-cognitivism''). I argue (...) for cognitivism and against non-cognitivism. First, I show that the distinction between competence and performance in current linguistics is as clearly made as ever it was, in spite of recent interest in linguistic processing modules. Second, I use these facts about the practice of theoretical linguistics to refute various proposals for a non-cognitivist construal of grammatical competence, and to support cognitivism by reflecting on the inapplicability of a multi-level account of linguistic competence. Cognitivism is then defended against several objections centring around the problems of rational integration and conceptualization of grammatical knowledge. Finally, the conception of competence argued for in relation to linguistics is placed in the larger context of cognitive science research and its implications for philosophy of mind. (shrink)

How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly (...) stated by any premise. They then test the validity of the conclusion by searching for alternative models that might refute the conclusion. The theory also resolves long-standing puzzles about reasoning, including how nonmonotonic reasoning occurs in daily life. The book reports experiments on all the main domains of deduction, including inferences based on prepositional connectives such as “if” and “or,” inferences based on relations such as “in the same place as,” inferences based on quantifiers such as “none,” “any,” and “only,” and metalogical inferences based on assertions about the true and the false. Where the two theories make opposite predictions, the results confirm the model theory and run counter to the formal rule theories. Without exception, all of the experiments corroborate the two main predictions of the model theory: inferences requiring only one model are easier than those requiring multiple models, and erroneous conclusions are usually the result of constructing only one of the possible models of the premises. (shrink)

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory, as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed—a motor command. This paper aims (...) to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference—behavioral modeling frameworks that descend, but are distinct, from OMCT—and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference. (shrink)

Critical notice of Andy Clark's "Associative Engines".