Linear Processing with Pregroups

Pregroup grammars have a cubic recognition algorithm. Here, we define a correct and complete recognition and parsing algorithm and give sufficient conditions for the algorithm to run in linear time. These conditions are satisfied by a large class of pregroup grammars, including grammars that handle coordinate structures and distant constituents.     

The probabilistic analysis of language acquisition: theoretical, computational, and experimental analysis

There is much debate over the degree to which language learning is governed by innate language-specific biases, or acquired through cognition-general principles. Here we examine the probabilistic language acquisition hypothesis on three levels: We outline a novel theoretical result showing that it is possible to learn the exact generative model underlying a wide class of languages, purely from observing samples of the language. We then describe a recently proposed practical framework, which quantifies natural language learnability, allowing specific learnability predictions to be made for the first time. In previous work, this framework was used to make learnability predictions for a wide variety of linguistic constructions, for which learnability has been much debated. Here, we present a new experiment which tests these learnability predictions. We find that our experimental results support the possibility that these linguistic constructions are acquired probabilistically from cognition-general principles.     

双内容样例学习的研究及重要启示

文章介绍了单内容样例与双内容样例的划分标准以及双内容样例在知识学习、技能和策略习得中应用研究的进展。作者从中获得启示,提出了根据学习域和示例域知识的熟悉程度组合不同学习难度的双内容样例并考察其学习效果、比较单内容与双内容样例学习效果的实验模式,并提出了双内容样例学习的三种认知加工模式。     

Natural language semantics in biproduct dagger categories

Biproduct dagger categories serve as models for natural language. In particular, the biproduct dagger category of finite dimensional vector spaces over the field of real numbers accommodates both the extensional models of predicate calculus and the intensional models of quantum logic. The morphisms representing the extensional meanings of a grammatical string are translated to morphisms representing the intensional meanings such that truth is preserved. Pregroup grammars serve as the tool that transforms a grammatical string into a morphism. The chosen linguistic examples concern negation, relative noun phrases, comprehension and quantifiers.     

What goes up may come down: perceptual process and knowledge access in the organization of complex visual patterns by young infants

The relationship between perceptual categorization and organization processes in 3‐ to 4‐month‐old infants was explored. The question was whether an invariant part abstracted during category learning could interfere with Gestalt organizational processes. Experiment 1 showed that the infants could parse a circle in accord with good continuation from visual patterns consisting of a circle and a complex polygon. In Experiments 2 and 3, however, this parsing was interfered with by a prior category familiarization experience in which infants were presented with visual patterns consisting of a pacman shape and a complex polygon. Part 1 of Experiments 2 and 3 showed that the infants recognized the pacman as familiar, and Part 2 demonstrated that the representation of the pacman blocked the subsequent parsing of the circle. The results suggest that a cognitive system of flexible feature creation can override organizational principles with which a perceptual system may come pre‐equipped.     

Example-based learning: New theoretical perspectives and use-inspired advances to a contemporary instructional approach

Decades of research has shown that example-based learning is an effective instructional strategy for learning new skills. The field of learning from examples is seeing a shift in focus towards more innovative and use-inspired research, in part because the use of examples for informal and formal learning purposes has mushroomed. This special issue comprises a set of eight papers in which students learned a procedural skill from worked examples or modeling examples. Each study characterizes a recent development towards more innovative example-based learning research. These developments are: (a) the integration of social-cognitive and cognitive example research, (b) the integration of example-based learning and analogical reasoning research, (c) the extension of traditional Cognitive Load Theory effects, (d) a greater focus on learning from (productive) errors, and (e) more research on individual differences. This special issue concludes with insightful commentary articles written by Prof. Dr. Katharina Scheiter and Prof. Dr. Richard Mayer.     

‘Ideal learning’ of natural language: Positive results about learning from positive evidence

Gold's [1967. Language identification in the limit. Information and Control, 16, 447-474] celebrated work on learning in the limit has been taken, by many cognitive scientists, to have powerful negative implications for the learnability of language from positive data (i.e., from mere exposure to linguistic input). This provides one, of several, lines of argument that language acquisition must draw on other sources of information, including innate constraints on learning. We consider an ‘ideal learner’ that applies a Simplicity Principle to the problem of language acquisition. The Simplicity Principle chooses the hypothesis that provides the briefest representation of the available data—here, the data are the linguistic input to the child. The Simplicity Principle allows learning from positive evidence alone, given quite weak assumptions, in apparent contrast to results on language learnability in the limit (e.g., Gold, 1967). These results provide a framework for reconsidering the learnability of various aspects of natural language from positive evidence, which has been at the center of theoretical debate in research on language acquisition and linguistics.     

Imitation without intentionality. Using string parsing to copy the organization of behaviour

A theory of imitation is proposed, string parsing, which separates the copying of behavioural organization by observation from an understanding of the cause of its effectiveness. In string parsing, recurring patterns in the visible stream of behaviour are detected and used to build a statistical sketch of the underlying hierarchical structure. This statistical sketch may in turn aid the subsequent comprehension of cause and effect. Three cases of social learning of relatively complex skills are examined, as potential cases of imitation by string parsing. Understanding the basic requirements for successful string parsing helps to resolve the conflict between mainly negative reports of imitation in experiments and more positive evidence from natural conditions. Since string parsing does not depend on comprehension of the intentions of other agents or the everyday physics of objects, separate tests of these abilities are needed even in animals shown to learn by imitation. Received: 11 January 1999 / Accepted after revision: 8 March 1999     

Who do you look like? Evidence of facial stereotypes for male names

The present research provides evidence that people use facial prototypes when they encounter different names. In Experiment 1, participants created face exemplars for fifteen common male names, subsets of which were endorsed as good examples by a second set of participants. These most typical faces were morphed to create face-name prototypes. In Experiment 2, participants matched one of the names to each of the prototype faces from Experiment 1. Participants’ matching choices showed convergence in naming the prototypes for many of the names. Experiment 3 utilized these same prototypes in a learning task designed to investigate if the face-name associations revealed in Experiment 2 impacted the learnability of the names. Participants learned face-name pairings that had a higher association (based on frequencies from Experiment 2) faster than pairings with a low association. Results suggest a more direct relationship between faces and names than has been previously proposed.     

The role of incremental parsing in syntactically conditioned word learning

In a series of three experiments, we use children’s noun learning as a probe into their syntactic knowledge as well as their ability to deploy this knowledge, investigating how the predictions children make about upcoming syntactic structure change as their knowledge changes. In the first two experiments, we show that children display a developmental change in their ability to use a noun’s syntactic environment as a cue to its meaning. We argue that this pattern arises from children’s reliance on their knowledge of verbs’ subcategorization frame frequencies to guide parsing, coupled with an inability to revise incremental parsing decisions. We show that this analysis is consistent with the syntactic distributions in child-directed speech. In the third experiment, we show that the change arises from predictions based on verbs’ subcategorization frame frequencies.     

Connectionist natural language parsing

The key developments of two decades of connectionist parsing are reviewed. Connectionist parsers are assessed according to their ability to learn to represent syntactic structures from examples automatically, without being presented with symbolic grammar rules. This review also considers the extent to which connectionist parsers offer computational models of human sentence processing and provide plausible accounts of psycholinguistic data. In considering these issues, special attention is paid to the level of realism, the nature of the modularity, and the type of processing that is to be found in a wide range of parsers.     

A computational learning model for metrical phonology

One of the major challenges to linguistic theory is the solution of what has been termed the "projection problem". Simply put, linguistics must account for the fact that starting from a data base that is both unsystematic and relatively small, a human child is capable of constructing a grammar that mirrors, for all intents and purposes, the adult system. In this article we shall address ourselves to the question of the learnability of a postulated subsystem of phonological structure: the stress system. We shall describe a computer program which is designed to acquire this subpart of linguistic structure. Our approach follows the "principles and parameters" model of Chomsky (1981a, b). This model is particularly interesting from both a computational point of view and with respect to the development of learning theories. We encode the relevant aspects of universal grammar (UG)--those aspects of linguistic structure that are presumed innate and thus present in every linguistic system. The learning process consists of fixing a number of parameters which have been shown to underlie stress systems and which should, in principle, lead the learner to the postulation of the system from which the primary linguistic data (i.e., the input to the learner) is drawn. We go on to explore certain formal and substantive properties of this learning system. Questions such as cross-parameter dependencies, determinism, subsets, and incremental versus all-at-once learning are raised and discussed in the article. The issues raised by this study provide another perspective on the formal structure of stress systems and the learnability of parameter systems in general.     

用户运动信息反馈形式对体感操作用户体验的影响——一项基于Kinect的可用性研究

体感交互是新兴的人机交互方式;当前,相关的人因学研究相对缺乏。本研究采用典型任务结合主观评价法,首次探索了用户运动信息反馈形式对体感交互用户体验的影响。笔者从易学性、控制性、情感与心理负荷四个方面,比较了有、无人形反馈形式对游戏体感菜单操作可用性的影响。结果发现,二者在心理负荷上无差异,无人形反馈在易学性上优于有人形,但有人形反馈在控制感上优于无人形,且更受用户喜爱。基于该结果,笔者建议在体感操作界面上使用有人形反馈。     

Implicit learning of a recursive rule in an artificial grammar

Participants performed an artificial grammar learning task, in which the standard finite state grammar (J. Verb. Learn. Verb. Behavior 6 (1967) 855) was extended with a recursive rule generating self-embedded sequences. We studied the learnability of such a rule in two experiments. The results verify the general hypothesis that recursivity can be learned in an artificial grammar learning task. However this learning seems to be rather based on recognising chunks than on abstract rule induction. First, performance was better for strings with more than one level of self-embedding in the sequence, uncovering more clearly the self-embedding pattern. Second, the infinite repeatability of the recursive rule application was not spontaneously induced from the training, but it was when an additional cue about this possibility was given. Finally, participants were able to verbalise their knowledge of the fragments making up the sequences-especially in the crucial front and back positions-, whereas knowledge of the underlying structure, to the extent it was acquired, was not articulatable. The results are discussed in relation to previous studies on the implicit learnability of complex and abstract rules.     

On Learnability of Restricted Classes of Categorial Grammars

In this paper we present learning algorithms for classes of categorial grammars restricted by negative constraints. We modify learning functions of Kanazawa [10] and apply them to these classes of grammars. We also prove the learnability of intersection of the class of minimal grammars with the class of k-valued grammars. Presented by Wojciech Buszkowski     

The neural basis of cognitive development: a constructivist manifesto

How do minds emerge from developing brains? According to "neural constructivism," the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: "constructive learning" minimizes the need for prespecification in accordance with recent neurobiological evidence that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning.     

Learning at a distance I. Statistical learning of non-adjacent dependencies

In earlier work we have shown that adults, young children, and infants are capable of computing transitional probabilities among adjacent syllables in rapidly presented streams of speech, and of using these statistics to group adjacent syllables into word-like units. In the present experiments we ask whether adult learners are also capable of such computations when the only available patterns occur in non-adjacent elements. In the first experiment, we present streams of speech in which precisely the same kinds of syllable regularities occur as in our previous studies, except that the patterned relations among syllables occur between non-adjacent syllables (with an intervening syllable that is unrelated). Under these circumstances we do not obtain our previous results: learners are quite poor at acquiring regular relations among non-adjacent syllables, even when the patterns are objectively quite simple. In subsequent experiments we show that learners are, in contrast, quite capable of acquiring patterned relations among non-adjacent segments-both non-adjacent consonants (with an intervening vocalic segment that is unrelated) and non-adjacent vowels (with an intervening consonantal segment that is unrelated). Finally, we discuss why human learners display these strong differences in learning differing types of non-adjacent regularities, and we conclude by suggesting that these contrasts in learnability may account for why human languages display non-adjacent regularities of one type much more widely than non-adjacent regularities of the other type.     

面向汉语认知与功能特征的语法逻辑

本文研究范畴语法的两种扩充,一是从认知特征角度的扩充,将范畴语法扩充为认知特征范畴语法,通过具有完全性的逻辑证明解决了一些不合语言事实的句子判别问题;二是从功能特征角度的扩充,提出逻辑推理的形式和进一步将二者统一的可能性问题。     

Leave Her out of It: Person‐Presentation of Strategies is Harmful for Transfer

A common practice in textbooks is to introduce concepts or strategies in association with specific people. This practice aligns with research suggesting that using “real‐world” contexts in textbooks increases students’ motivation and engagement. However, other research suggests this practice may interfere with transfer by distracting students or leading them to tie new knowledge too closely to the original learning context. The current study investigates the effects on learning and transfer of connecting mathematics strategies to specific people. A total of 180 college students were presented with an example of a problem‐solving strategy that was either linked with a specific person (e.g., “Juan's strategy”) or presented without a person. Students who saw the example without a person were more likely to correctly transfer the novel strategy to new problems than students who saw the example presented with a person. These findings are the first evidence that using people to present new strategies is harmful for learning and transfer.     

Serial position phenomena: Training and retrieval effects

With successive free recall lists primacy items are usually among the first to be reported on the initial list. Recency items will then take over and be first reported on later lists. This retrieval shift was studied under varied list conditions designed to counteract ordinary position effects, and proved to be a stable and resistent effect. One experiment had subjects practice on five different free recall lists over three trials, and the results agreed with the hypothesis that primacy reduction is caused by proactive interference rather than by the primacy to recency report shift. Experiments of the usual one-session laboratory type have consistently failed to show practice effects on serial lists with incompatible spatial and temporal order cues. In a case study of five subjects examined over a period of three months only slight improvement on single-trial lists was observed. However, when naive subjects were given four successive trials with the same type of cue-conflict list, prominent practice effects were easily demonstrated. Observations confirmed the assumption that repeated presentations of items located in middle list positions may counteract the privilege of primacy and recency positions. When repetitions were made within contracting and expanding lists, the results proved that active anchoring, making itself visible as primacy effects, is feasible with contracting lists but difficult with expanding lists. Active performance of list learning strategies generally results in primacy effects; whereas passive shortcut procedures, in learning and retrieval of information, produce recency effects. Predominant recency effects are symptoms of difficult task situations only partially mastered by the learner; primacy effects point to more successful elaboration. Overall, serial position effects do not seem to be due to structural memory stores so much as to the working of cognitive strategy factors. A problem-solving theory was presented as an alternative to information-processing models of serial learning and memory.