Could there be a cognitive zombie – that is, a creature with the capacity for cognition, but no capacity for consciousness? Searle argues that there cannot be a cognitive zombie because there cannot be an intentional zombie: on this view, there is a connection between consciousness and cognition that is derived from a more fundamental connection between consciousness and intentionality. However, I argue that there are good empirical reasons for rejecting the proposed connection between consciousness and intentionality. Instead, I argue (...) that there is a connection between consciousness and cognition that is derived from a more fundamental connection between consciousness and rationality. On this view, there cannot be a cognitive zombie because there cannot be a rational zombie. (shrink)

The role of metalinguistic ability in L2 development is seriously underestimated. It may be seen both (1) as a means of initiating or boosting the flow of primary linguistic data and (2) as a generator of substitute knowledge (derived, but epistemologically distinct from domain-specific knowledge) that may compete with or compensate for perceived gaps in the learners current underlying competence. It cannot serve as a simple means of distinguishing the rival theoretical positions.

Evidence is presented from a polyglot savant to suggest that double dissociations between linguistic and nonverbal abilities are more important than Müller's target article implies. It is also argued that the special nature of syntax makes its assimilation to other aspects of language or to nonhuman communication systems radically implausible.

A theoretical framework Is presented that distinguishes among three knowledge sources that form the basis for generative performance. The three knowledge sources, termed conceptual, procedural, and utilizational competence, were implemented as a computational model that derives plans for counting procedures. In a previous analysis, Greeno, Riley, and Gelman (1984) developed a characterization of the conceptual competence (implicit understanding of general concepts and principles) associated with the skill of counting and related conceptual competence to various models of performance. In the current (...) work all three knowledge sources are formalized in a computer program (COUNTPLAN) that generates planning nets of counting procedures. The sufficiency of COUNTPLAN's knowledge components is demonstrated through its capacity to generate new plans for counting in novel settings from a core of conceptual competence. The utility of COUNTPLAN to facilitate the distinction between hypotheses of competence and hypotheses of performance is discussed. (shrink)

Suppose that two competing norms, N1 and N2, can be identified such that a given person’s response can be interpreted as correct according to N1 but incorrect according to N2. Which of these two norms, if any, should one use to interpret such a response? In this paper we seek to address this fundamental problem by studying individual variation in the interpretation of conditionals by establishing individual profiles of the participants based on their case judgments and reflective attitudes. To investigate (...) the participants’ reflective attitudes we introduce a new experimental paradigm called the Scorekeeping Task. As a case study, we identify the participants who follow the Suppositional Theory of conditionals (N1) versus Inferentialism (N2) and investigate to what extent internally consistent competence models can be reconstructed for the participants on this basis. After extensive empirical investigations, an apparent reasoning error with and-to-if inferences was found in one of these two groups. The implications of this case study for debates on the proper role of normative considerations in psychology are discussed. (shrink)

We owe most scientific knowledge to methods of inquiry that are never formally analyzed. The analysis of behavior does not call for hypothetico-deductive methods. Statistics, taught in lieu of scientific method, is incompatible with major features of much laboratory research. Squeezing significance out of ambiguous data discourages the more promising step of scrapping the experiment and starting again. As a consequence, psychologists have taken flight from the laboratory. They have fled to Real People and the human interest of “real life,” (...) to Mathematical Models and the elegance of symbolic treatments, to the Inner Man and the explanatory preoccupation with inferred internal mechanisms, and to Laymanship and its appeal to “common sense.” An experimental analysis provides an alternative to these divertissements.The “theories” to which objection is raised here are not the basic assumptions essential to any scientific activity or statements that are not yet facts, but rather explanations which appeal to events taking place somewhere else, at some other level of observation, described in different terms, and measured, if at all, in different dimensions. Three types of learning theories satisfy this definition: physiological theories attempting to reduce behavior to events in the nervous system; mentalistic theories appealing to inferred inner events; and theories of the Conceptual Nervous System offered as explanatory models of behavior. It would be foolhardy to deny the achievements of such theories in the history of science. The question of whether they are necessary, however, has other implications.Experimental material in three areas illustrates the function of theory more concretely. Alternatives to behavior ratios, excitatory potentials, and so on demonstrate the utility of rate or probability of response as the basic datum in learning. Functional relations between behavior and environmental variables provide an account of why learning occurs. Activities such as preferring, choosing, discriminating, and matching can be dealt with solely in terms of behavior, without referring to processes in another dimensional system. The experiments are not offered as demonstrating that theories are not necessary but to suggest an alternative. Theory is possible in another sense. Beyond the collection of uniform relationships lies the need for a formal representation of the data reduced to a minimal number of terms. A theoretical construction may yield greater generality than any assemblage of facts; such a construction will not refer to another dimensional system. (shrink)

The computation of scalar implicatures is sometimes costly relative to basic meanings. Among the costly computations are those that involve strengthening `some' to `not all' and strengthening inclusive disjunction to exclusive disjunction. The opposite is true for some other cases of strengthening, where the strengthened meaning is less costly than its corresponding basic meaning. These include conjunctive strengthenings of disjunctive sentences (e.g., free-choice inferences) and exactly-readings of numerals. Assuming that these are indeed all instances of strengthening via implicature/exhaustification, the puzzle (...) is to explain why strengthening sometimes increases costs while at other times it decreases costs. I develop a theory of processing costs that makes no reference to the strengthening mechanism or to other aspects of the derivation of the sentence's form/meaning. Instead, costs are determined by domain-general considerations of the grammar's output, and in particular by aspects of the meanings of ambiguous sentences and particular ways they update the context. Specifically, I propose that when the hearer has to disambiguate between a sentence's basic and strengthened meaning, the processing cost of any particular choice is a function of (i) a measure of the semantic complexity of the chosen meaning and (ii) a measure of how much relevant uncertainty it leaves behind in the context. I measure semantic complexity with Boolean Complexity in the propositional case and with semantic automata in the quantificational case, both of which give a domain-general measure of the minimal representational complexity needed to express the given meaning. I measure relevant uncertainty with the information-theoretic notion of entropy; this domain-general measure formalizes how `far' the meaning is from giving a complete answer to the question under discussion, and hence gives an indication of how much representational complexity is yet to come. Processing costs thus follow from domain-general considerations of current and anticipated representational complexity. The results might also speak to functional motivations for having strengthening mechanisms in the first place. Specifically, exhaustification allows language users to use simpler forms than would be available without it to both resolve relevant uncertainties and convey complex meanings. (shrink)

Müller's review of the neuroscientific evidence undermines nativist claims for autonomous syntax and the argument from the poverty of the stimulus. Generativists will appeal to data from language acquisition, but here too there is growing evidence against the nativist position. Epigenetic naturalism, the developmental alternative to nativism, can be extended to epigenetic socionaturalism, acknowledging the importance of sociocultural processes in language and cognitive development.

This paper compares and contrasts Mencius's moral philosophy with recent development in cognitive science regarding mental capacity to understand moral rules and principles. Several cognitive scientists argue that the human mind has innate cognitive and emotive foundations of morality. In this paper, Mencius's moral theory is interpreted from the perspective of faculty psychology and cognitive modularity, a theoretical hypothesis in cognitive science in which the mind is understood as a system of specialized mental components. Specifically, Mencius's Four Beginnings (the basic (...) human emotions that serve as the foundations of morality) are interpreted as vertical faculties, comparable to Scottish philosopher Thomas Reid's moral faculties. (shrink)

Since the publication of Fodor's (1983) The Modularity of Mind, there have been quite a few discussions of cognitive modularity among cognitive scientists. Generally, in those discussions, modularity means a property of specialized cognitive processes or a domain-specific body of information. In actuality, scholars understand modularity in many different ways. Different characterizations of modularity and modules were proposed and discussed, but they created misunderstanding and confusion. In this article, I classified and analyzed different approaches to modularity and argued for the (...) unity of modularity. Modularity is a multidimensional property consisting of features from several dimensions specifying different aspects of cognition. Among those, there are core features of modularity, and these core features form a cross-dimensional unity. Despite the diverse and liberal characterizations, modularity contributes to cognitive science because of the unity of the core features. (shrink)

Rumelhart and McClelland's chapter about learning the past tense created a degree of controversy extraordinary even in the adversarial culture of modern science. It also stimulated a vast amount of research that advanced the understanding of the past tense, inflectional morphology in English and other languages, the nature of linguistic representations, relations between language and other phenomena such as reading and object recognition, the properties of artificial neural networks, and other topics. We examine the impact of the Rumelhart and McClelland (...) model with the benefit of 25 years of hindsight. It is not clear who “won” the debate. It is clear, however, that the core ideas that the model instantiated have been assimilated into many areas in the study of language, changing the focus of research from abstract characterizations of linguistic competence to an emphasis on the role of the statistical structure of language in acquisition and processing. (shrink)

In this paper we argue that ecological evolutionary developmental biology accounts of cognitive modernity are compatible with cultural evolution theories of language built upon iterated learning models. Cultural evolution models show that the emergence of near universal properties of language do not require the preexistence of strong specific constraints. Instead, the development of general abilities, unrelated to informational specificity, like the copying of complex signals and sharing of communicative intentions is required for cultural evolution to yield specific properties, such as (...) language structure. We argue that eco-evo-devo provides the appropriate conceptual background to ground an account for the many interconnected genetic, environmental and developmental factors that facilitated the emergence of an organic system able to develop language through the iterated transmission of information. We use the concept of niche construction to connect evolutionary developmental accounts for sensory guided motor capacities and cultural evolution guided by iterated learning models. This integrated theoretical model aims to build bridges between biological and cultural approaches. (shrink)

This paper proposes a causal-dispositional account of rule-following as it occurs in reasoning and intentional agency. It defends this view against Kripke’s (1982) objection to dispositional accounts of rule-following, and it proposes a solution to the problem of deviant causal chains. In the first part, I will outline the causal-dispositional approach. In the second part, I will follow Martin and Heil’s (1998) realist response to Kripke’s challenge. I will propose an account that distinguishes between two kinds of rule-conformity and two (...) kinds of rule-following, and I will defend the realist approach against two challenges that have recently been raised by Handfield and Bird (2008). In the third part, I will turn to the problem of deviant causal chains, and I will propose a new solution that is partly based on the realist account of rule-following. (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)