General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory—the component of short‐term memory used for temporary storage and manipulation of information. In this study, we consider the relationship between working memory and regularization of linguistic variation. Regularization is a well‐documented process whereby (...) languages become less variable (on some dimension) over time. This process has been argued to be driven by the behavior of individual language users, but the specific mechanism is not agreed upon. Here, we use an artificial language learning experiment to investigate whether limitations in working memory during either language learning or language production drive regularization behavior. We find that taxing working memory during production results in the loss of all types of variation, but the process by which random variation becomes more predictable is better explained by learning biases. A computational model offers a potential explanation for the production effect using a simple self‐priming mechanism. (shrink)

For decades, interdisciplinary research efforts have accumulated insights that diminish the significance of the classic nature versus nurture dichotomy, instead calling for a nuanced, multifactorial approach to ontogeny. Similarly, the role of genes in both phylogeny and ontogeny, once seen as rather deterministic, is now conceptualized as highly dependent on environmental factors, including behavior. Linguistic theories have, in principle, made an effort to incorporate these changing views. However, the central claim of the given paper is that this apparent compliance with (...) biological insights remains superficial. As such, considerable disconnects between linguistic theory and what is known about the biological underpinnings of complex traits persist, negatively impacting pertinent views on language acquisition, language universals and the evolution of language. Given the breadth of these fields of study, the aim of this paper is to tackle the root of the problem: It begins by sketching out linguistic nativism as conceptualized within generativism, pointing to aspects within this position that stand in conflict with the interdisciplinary literature. It will then review select areas of research in a succinct manner in order to substantiate the criticism and characterize the counterposition as found within the biological sciences. The paper will culminate in addressing these disconnects on conceptual grounds, i.e. invoking the term emergence as employed in neuroscience as a possible means to reconcile those biological insights with linguistic nativism. (shrink)

While endorsing Evans & Levinson's (E&L's) call for rigorous documentation of variation, we defend the idea of Universal Grammar as a toolkit of language acquisition mechanisms. The authors exaggerate diversity by ignoring the space of conceivable but nonexistent languages, trivializing major design universals, conflating quantitative with qualitative variation, and assuming that the utility of a linguistic feature suffices to explain how children acquire it.

Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)

Connectionist models aiming to reveal the mechanisms of atypical development must in their undamaged form constitute plausible models of normal development and follow a developmental trajectory that matches empirical data. Constructivist models that adapt their structure to the learning task satisfy this demand. They are therefore more informative in the study of atypical development than the static models employed by Thomas & Karmiloff-Smith (T&K-S).

An influential view of the nature of the language system is that of an evolved biological system in which a set of rules is combined with a lexicon that contains the words of the language together with a representation of their context. Alternative views, usually based on connectionist modeling, attempt to explain the structure of language on the basis of complex associative processes. Here, I put forward a third view that stresses experience-dependent structural development of the brain circuits supporting language (...) as a core principle of the organization of the language system. In this view, embodied in a recent neuroconstructivist neural network of past tense development and processing, initial domain-general predispositions enable the development of functionally specialized brain structures through interactions between experience-dependent brain development and statistical learning in a structured environment. Together, these processes shape a biological adult language system that appears to separate into distinct mechanism for processing rules and exceptions, whereas in reality those subsystems co-develop and interact closely. This view puts experience-dependent brain development in response to a specific language environment at the heart of understanding not only language development but adult language processing as well. (shrink)

For native English readers, masked presentations of past-tense verb primes produce faster lexical decision latencies to their present-tense targets than orthographically related or unrelated primes. This facilitation observed with morphologically related prime-target pairs is generally taken as evidence for strong connections based on morphological relationships in the L1 lexicon. It is unclear, however, if similar, morphologically based, connections develop in non-native lexicons. Several earlier studies with L2 English readers have reported mixed results. The present experiments examine whether past-tense verb primes (...) significantly facilitate target lexical decisions for Japanese-English bilinguals beyond any facilitation provided by prime-target orthographic similarity. Overall, past-tense verb primes facilitated lexical decisions to their present-tense targets relative to both orthographically related and unrelated primes. Replicating previous masked priming experiments with L2 readers, orthographically related primes also facilitated target recognition relative to unrelated primes, confirming that orthographic similarity facilitates L2 target recognition. The additional facilitation from past-tense verb primes beyond that provided by orthographic primes suggests that, in the L2 English lexicon, connections based on morphological relationships develop in a way that is similar to how they develop in the L1 English lexicon even though the connections and processing of lower level, lexical/orthographic information may differ. Further analyses involving L2 proficiency revealed that as L2 proficiency increased, orthographic facilitation was reduced, indicating that there is a decrease in the fuzziness in orthographic representations in the L2 lexicon with increased proficiency. (shrink)

Dutch, like other Germanic languages, disposes of two strategies to express past tense: the strong inflection (e.g., rijden – reed ‘drive – drove’) and the weak inflection (spelen – speelde ‘play – played’). This distinction is for the most part lexically determined in that each verb occurs in one of the two inflections. Diachronically the system is in flux though, with the resilience of some verbs being mainly driven by frequency. Synchronically this might result in variable verbs (e.g., schuilen – (...) schuilde/school ‘hide – hid’ or raden – raadde/ried ‘guess – guessed’). This diachronic (1300–2000) corpus study shows that this variation is not haphazard, but that semantic factors are at play. We see two such effects. First of all, synchronically, the variation is exapted in an iconic manner to express aspect: durative meanings tend to be expressed by longer verb forms and punctual meanings tend to be expressed by shorter verb forms. Secondly, we see that metaphorical meanings come to be associated within obsolescent inflectional forms, as predicted by Kuryłowicz’s “fourth law of analogy”. (shrink)

It is often assumed that similar domain-specific behavioural impairments found in cases of adult brain damage and developmental disorders correspond to similar underlying causes, and can serve as convergent evidence for the modular structure of the normal adult cognitive system. We argue that this correspondence is contingent on an unsupported assumption that atypical development can produce selective deficits while the rest of the system develops normally (Residual Normality), and that this assumption tends to bias data collection in the field. Based (...) on a review of connectionist models of acquired and developmental disorders in the domains of reading and past tense, as well as on new simulations, we explore the computational viability of Residual Normality and the potential role of development in producing behavioural deficits. Simulations demonstrate that damage to a developmental model can produce very different effects depending on whether it occurs prior to or following the training process. Because developmental disorders typically involve damage prior to learning, we conclude that the developmental process is a key component of the explanation of endstate impairments in such disorders. Further simulations demonstrate that in simple connectionist learning systems, the assumption of Residual Normality is undermined by processes of compensation or alteration elsewhere in the system. We outline the precise computational conditions required for Residual Normality to hold in development, and suggest that in many cases it is an unlikely hypothesis. We conclude that in developmental disorders, inferences from behavioural deficits to underlying structure crucially depend on developmental conditions, and that the process of ontogenetic development cannot be ignored in constructing models of developmental disorders. Key Words: Acquired and developmental disorders; connectionist models; modularity; past tense; reading. (shrink)

Human participants and recurrent (“connectionist”) neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular (“strong”) classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks’ encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can (...) be directly compared with the mechanisms of non-connectionist, rule-based accounts. The results reveal that the networks “contain” structures related to mechanisms posited by rule-based models, partly vindicating the insights of these models. On the other hand, they support the one mechanism (OM), as opposed to the more than one mechanism (MOM), view of symbolic abstraction by showing how the appearance of MOM behavior can arise emergently from one underlying set of principles. The key new contribution of this study is to show that dynamical systems theory can allow us to explicitly characterize the relationship between the two perspectives in implemented models. (shrink)

Phonemes have variant pronunciations depending on context. For instance, in American English, the [t] in pat [pæt] and the [d] in pad [pæd] are both realized with a tap [ɾ] when the –ing suffix is attached, [pæɾɪŋ]. We show that despite greater distributional and acoustic support for the [t]-tap alternation, 12-month-olds successfully relate taps to stems with a perceptually-similar final [d], not the dissimilar final-[t]. Thus, distributional learning of phonological alternations is constrained by infants' preference for the alternation of perceptually-similar (...) segments. Further, the ability to relate variant surface forms emerges between 8- and 12-months. Our findings of biased learning provide further empirical support for a role for perceptual similarity in the acquisition of linguistically-relevant categories. We discuss the implications of our findings for phonological theory, language acquisition and models of the mental lexicon. (shrink)

Cognitive science depends on abstractions made from the complex reality of human behaviour. Cognitive scientists typically wish the abstractions in their theories to be universals, but seldom attend to the ontology of universals. Two sorts of universal, resulting from Galilean abstraction and materialist abstraction respectively, are available in the philosophical literature: the abstract universal—the one-over-many universal—is the universal conventionally employed by cognitive scientists; in contrast, a concrete universal is a material entity that can appear within the set of entities it (...) describes, of which it represents the essential, paradigmatic case. The potential role of concrete universals in cognitive science is discussed. (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)

The input to phonological reasoning are alternations, that is, variations in the pronunciation of related words, such as in electri[k] ‐ electri[s]‐ity. But phonologists cannot agree what counts as a relevant alternation: the issue is highly contentious despite a research record of over 50 years. We believe that the experimental setup presented may contribute to this debate based on a kind of evidence that was not brought to bear to date. Our experiment was thus designed to distinguish between alternations where (...) phonological computation plays no role, and those where it has contributed to language production. The design manipulates two factors that to date have not been considered in experimental studies of language production: linguistic complexity and alternation specificity. The former is understood as extra processing demands issued by two types of linguistic activity, morphosyntactic and phonological. Our results show that reaction time latencies are longer when participants are burdened with both morphosyntactic and phonological tasks than when they carry out just a morphosyntactic task, and they are still shorter in absence of both types of demands. These results allowed us to address alternation specificity, that is, the fact that different alternations (within a language or across languages) may be driven by different production routines (an idea that is consensual among linguists but underdeveloped in the psycholinguistic literature). Our study shows that four different alternations in French produce alternation‐specific signatures in reaction time latencies. These findings may thus redound to the advantage of psycholinguistic studies by identifying two new factors, as well as produce results that speak to the linguistic quarrels. (shrink)

Many generativist accounts argue for very early knowledge of inflection on the basis of very low rates of person/number marking errors in young children's speech. However, studies of Spanish and Brazilian Portuguese have revealed that these low overall error rates actually hide important differences across the verb paradigm. The present study investigated children's production of person/number marked verbs by eliciting present tense verb forms from 82 native Finnish-speaking children aged 2;2–4;8 years. Four main findings were observed: Rates of person/number marking (...) errors were higher in low-frequency person/number contexts, even excluding children who showed no evidence of having learned the relevant morpheme, most errors involved the use of higher frequency forms in lower frequency person/number contexts, error rates were predicted not only by the frequency of person/number contexts but also by the frequency of individual “ready-inflected” lexical target forms, and for low-frequency verbs, lower error rates were observed for verbs with high phonological neighborhood density. It is concluded that any successful account of the development of verb inflection will need to incorporate both rote-storage and retrieval of individual inflected forms and phonological analogy across them. (shrink)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

In a continuation of the conversation with Fitch, Chomsky, and Hauser on the evolution of language, we examine their defense of the claim that the uniquely human, language-specific part of the language faculty (the “narrow language faculty”) consists only of recursion, and that this part cannot be considered an adaptation to communication. We argue that their characterization of the narrow language faculty is problematic for many reasons, including its dichotomization of cognitive capacities into those that are utterly unique and those (...) that are identical to nonlinguistic or nonhuman capacities, omitting capacities that may have been substantially modified during human evolution. We also question their dichotomy of the current utility versus original function of a trait, which omits traits that are adaptations for current use, and their dichotomy of humans and animals, which conflates similarity due to common function and similarity due to inheritance from a recent common ancestor. We show that recursion, though absent from other animals’ communications systems, is found in visual cognition, hence cannot be the sole evolutionary development that granted language to humans. Finally, we note that despite Fitch et al.’s denial, their view of language evolution is tied to Chomsky’s conception of language itself, which identifies combinatorial productivity with a core of “narrow syntax.” An alternative conception, in which combinatoriality is spread across words and constructions, has both empirical advantages and greater evolutionary plausibility. q 2005 Elsevier B.V. All rights reserved. (shrink)

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that (...) are being developed by a number of authors. (shrink)

One of the central debates in the cognitive science of language has revolved around the nature of human linguistic competence. Whether syntactic competence should be characterized by abstract hierarchical structures or reduced to surface linear strings has been actively debated, but the nature of morphological competence has been insufficiently appreciated despite the parallel question in the cognitive science literature. In this paper, in order to investigate whether morphological competence should be characterized by abstract hierarchical structures, we conducted the crowdsourced acceptability (...) judgment experiment on morphologically complex words and evaluated five computational models of morphological competence against human acceptability judgments: Character Markov Models (Character), Syllable Markov Models (Syllable), Morpheme Markov Models (Morpheme), Hidden Markov Models (HMM), and Probabilistic Context-Free Grammars (PCFG). Our psycholinguistic experimentation and computational modeling demonstrated that "morphous" computational models with morpheme units outperformed "amorphous" computational models without morpheme units and, importantly, PCFG with hierarchical structures most accurately explained human acceptability judgments on several evaluation metrics, especially for morphologically complex words with nested morphological structures. Those results strongly suggest that human morphological competence should be characterized by abstract hierarchical structures internally generated by the grammar, not reduced to surface linear strings externally attested in large corpora. (shrink)

Inflectional morphology has been taken as a paradigmatic example of rule-governed grammatical knowledge (Pinker, 1999). The plausibility of this claim may be related to the fact that it is mainly based on studies of English, which has a very simple inflectional system. We examined the representation of inflectional morphology in Serbian, which encodes number, gender, and case for nouns. Linguists standardly characterize this system as a complex set of rules, with disagreements about their exact form. We present analyses of a (...) large corpus of nouns which showed that, as in English, Serbian inflectional morphology is quasiregular: It exhibits numerous partial regularities creating neighborhoods that vary in size and consistency. We then asked whether a simple connectionist network could encode this statistical information in a manner that also supported generalization. A network trained on 3,244 Serbian nouns learned to produce correctly inflected phonological forms from a specification of a word's lemma, gender, number, and case, and generalized to untrained cases. The model's performance was sensitive to variables that also influence human performance, including surface and lemma frequency. It was also influenced by inflectional neighborhood size, a novel measure of the consistency of meaning to form mapping. A word-naming experiment with native Serbian speakers showed that this measure also affects human performance. The results suggest that, as in English, generating correctly inflected forms involves satisfying a small number of simultaneous probabilistic constraints relating form and meaning. Thus, common computational mechanisms may govern the representation and use of inflectional information across typologically diverse languages. (shrink)

The study of human intelligence was once dominated by symbolic approaches, but over the last 30 years an alternative approach has arisen. Symbols and processes that operate on them are often seen today as approximate characterizations of the emergent consequences of sub- or nonsymbolic processes, and a wide range of constructs in cognitive science can be understood as emergents. These include representational constructs (units, structures, rules), architectural constructs (central executive, declarative memory), and developmental processes and outcomes (stages, sensitive periods, neurocognitive (...) modules, developmental disorders). The greatest achievements of human cognition may be largely emergent phenomena. It remains a challenge for the future to learn more about how these greatest achievements arise and to emulate them in artificial systems. (shrink)

We share with Anderson & Lebiere (A&L) (and with Newell before them) the goal of developing a domain-general framework for modeling cognition, and we take seriously the issue of evaluation criteria. We advocate a more focused approach than the one reflected in Newell's criteria, based on analysis of failures as well as successes of models brought into close contact with experimental data. A&L attribute the shortcomings of our parallel-distributed processing framework to a failure to acknowledge a symbolic level of thought. (...) Our framework does acknowledge a symbolic level, contrary to their claim. What we deny is that the symbolic level is the level at which the principles of cognitive processing should be formulated. Models cast at a symbolic level are sometimes useful as high-level approximations of the underlying mechanisms of thought. The adequacy of this approximation will continue to increase as symbolic modelers continue to incorporate principles of parallel distributed processing. (shrink)

Some empirical evidence in the artificial language acquisition literature has been taken to suggest that statistical learning mechanisms are insufficient for extracting structural information from an artificial language. According to the more than one mechanism (MOM) hypothesis, at least two mechanisms are required in order to acquire language from speech: (a) a statistical mechanism for speech segmentation; and (b) an additional rule-following mechanism in order to induce grammatical regularities. In this article, we present a set of neural network studies demonstrating (...) that a single statistical mechanism can mimic the apparent discovery of structural regularities, beyond the segmentation of speech. We argue that our results undermine one argument for the MOM hypothesis. (shrink)

In a continuation of the conversation with Fitch, Chomsky, and Hauser on the evolution of language, we examine their defense of the claim that the uniquely human, language-specific part of the language faculty (the “narrow language faculty”) consists only of recursion, and that this part cannot be considered an adaptation to communication. We argue that their characterization of the narrow language faculty is problematic for many reasons, including its dichotomization of cognitive capacities into those that are utterly unique and those (...) that are identical to nonlinguistic or nonhuman capacities, omitting capacities that may have been substantially modified during human evolution. We also question their dichotomy of the current utility versus original function of a trait, which omits traits that are adaptations for current use, and their dichotomy of humans and animals, which conflates similarity due to common function and similarity due to inheritance from a recent common ancestor. We show that recursion, though absent from other animals’ communications systems, is found in visual cognition, hence cannot be the sole evolutionary development that granted language to humans. Finally, we note that despite Fitch et al.’s denial, their view of language evolution is tied to Chomsky’s conception of language itself, which identifies combinatorial productivity with a core of “narrow syntax.” An alternative conception, in which combinatoriality is spread across words and constructions, has both empirical advantages and greater evolutionary plausibility. q 2005 Elsevier B.V. All rights reserved. (shrink)

Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at ages 2 to 3 (Aksu-Koç & Slobin, 1985; Nakipoğlu, Uzundag, & Sarıgül, 2021). So far, however, we know very little about children's understanding of causatives with novel verbs. In the present study, we asked: (a) (...) When does the generalization of causative morphology in a novel context emerge? and (b) What role does child-directed input play in this development? To answer the first question, we conducted comprehension-judgment experiments with children aged 2;6–6;11 using pseudo-verbs (Study 1 & 2). Results showed that children preferred the Turkish causative suffix -DIr over an unrelated or no suffix to denote caused events earliest at age 4;10. To answer the second question, we analyzed child-directed speech from a longitudinal corpus of Turkish language acquisition (Study 3). Results showed that when addressing children younger than age 3, caregivers used the -DIr suffix with little variation considering the overall variability of verbs they could utter. Overall, these findings suggest that productivity with morphological causatives in a novel context emerges in a later stage of acquisition. This later development might partly be accounted for by the insufficient variation of morphological causatives in the early input. (shrink)

Is formal simplicity a guide to learning in humans, as simplicity is said to be a guide to the acceptability of theories in science? Does simplicity determine the difficulty of various learning tasks? I argue that, similarly to how scientists sometimes preferred complex theories when this facilitated calculations, results from perception, learning and reasoning suggest that formal complexity is generally unrelated to what is easy to learn and process by humans, and depends on assumptions about available representational and processing primitives. (...) “Simpler” hypotheses are preferred only when they are also easier to process. Historically, “simpler”, easier‐to‐process, scientific theories might also be preferred if they are transmitted preferentially. Empirically viable complexity measures should build on the representational and processing primitives of actual learners, even if explanations of their behaviour become formally more complex. (shrink)

Evidence from aphasia is considered that leads to a distinction between abstract and concrete thought processes and hence for a distinction between rules and similarity. It is argued that perceptual classification is inherently a rule-following procedure and these rules are unable to be followed when a patient has difficulty with name comprehension and retrieval.

A well-trod debate at the nexus of cognitive science and linguistics, the so-called past tense debate, has examined how rules and exceptions are individually acquired. However, this debate focuses primarily on individual mechanisms in learning, saying little about how rules and exceptions function from a sociolinguistic perspective. To remedy this, we use agent-based models to examine how rules and exceptions function across populations. We expand on earlier work by considering how repeated interaction and cultural transmission across speakers affects the dynamics (...) of rules and exceptions in language, measuring linguistic outcomes within a social system rather than focusing individual learning outcomes. We consider how population turnover and growth effect linguistic rule dynamics in large and small populations, showing that this method has considerable potential particularly in probing the mechanisms underlying the linguistic niche hypothesis. (shrink)

By around the age of 5½, many children in the United States judge that numbers never end, and that it is always possible to add 1 to a set. These same children also generally perform well when asked to label the quantity of a set after one object is added (e.g., judging that a set labeled “five” should now be “six”). These findings suggest that children have implicit knowledge of the “successor function”: Every natural number, n, has a successor, n (...) + 1. Here, we explored how children discover this recursive function, and whether it might be related to discovering productive morphological rules that govern language‐specific counting routines (e.g., the rules in English that represent base‐10 structure). We tested 4‐ and 5‐year‐old children’s knowledge of counting with three tasks, which we then related to (a) children’s belief that 1 can always be added to any number (the successor function) and (b) their belief that numbers never end (infinity). Children who exhibited knowledge of a productive counting rule were significantly more likely to believe that numbers are infinite (i.e., there is no largest number), though such counting knowledge was not directly linked to knowledge of the successor function, per se. Also, our findings suggest that children as young as 4 years of age are able to implement rules defined over their verbal count list to generate number words beyond their spontaneous counting range, an insight which may support reasoning over their acquired verbal count sequence to infer that numbers never end. (shrink)

The debate over how best to characterize inflectional morphology has been couched largely in terms of the “dual-mechanism” approach described in Pinker (Words and rules: the ingredients of language, Basic Books, 1999) versus “single-mechanism” connectionist approaches derived from Rumelhart and McClelland (On learning past tenses of English verbs, MIT, 1986). There are, however, other single-mechanism approaches. The exemplar-based or analogical models of Daelemans et al. (TimBL: Tilburg Memory-Based Learner, version 4.3 reference guide, ILK, 2002) and Skousen (Analogical modeling of language, (...) Kluwer Academic, 1989) also model inflectional usage accurately within a single-mechanism. The most striking theoretical claim peculiar to these purely analogical models is that they do not posit any resident linguistic generalizations for processing language. Instead they process new instances of usage by comparing them systematically to remembered instances of previous usage. Based on a comparison of their Minimal Generalization Model with an adaptation of Nosofsky's (Journal of Mathematical Psychology 34: 393–418, 1990) Generalized Context Model, Albright and Hayes (Cognition 90: 119–161, 2003) argue that such purely analogical models are intrinsically inadequate for modeling the English past tense. This paper shows, however, that Skousen's (Analogical modeling of language, Kluwer Academic, 1989) Analogical Model performs as well as the Minimal Generalization Model. The implications of these results for cognitive linguistics are discussed. (shrink)

Computational models will play an important role in our understanding of human higher‐order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher‐order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do; (b) the breadth of situations in which it can do so; and (c) the parsimony of the mechanisms it posits. This article argues that fits of (...) models to quantitative experimental data, although valuable for other reasons, do not address these criteria. Further, using analogies with other sciences, the history of cognitive science, and examples from modern‐day research programs, this article identifies five activities that have been demonstrated to play an important role in our understanding of human higher‐order cognition. These include modeling within a cognitive architecture, conducting artificial intelligence research, measuring and expanding a model's ability, finding mappings between the structure of different domains, and attempting to explain multiple phenomena within a single model. (shrink)