The paper proposes a set of principles and a general architecture that may explain how language and meaning may originate and complexify in a group of physically grounded distributed agents. An experimental setup is introduced for concretising and validating specific mechanisms based on these principles. The setup consists of two robotic heads that watch a scene in which a robot moves around in its ecosystem. The first results from experiments showing the emergence of distinctions, of a lexicon, and of primitive syntactic structures are reported. 1 Introduction Artificial Intelligence research has made remarkable progress the last decades by showing how operations over symbolic models may explain various aspects of intelligent behavior, such as planning, problem solving, natural language processing, etc. However, the problem of the origin of these symbolic models has so far not been adequately addressed. Most of the time it is the programmer who designs formalisms and datastructures, ...

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Psycholinguistic research has shown that the influence of abstract syntactic knowledge on performance is shaped by particular sentences that have been experienced. To explore this idea, the authors applied a connectionist model of sentence production to the development and use of abstract syntax. The model makes use of (a) error-based learning to acquire and adapt sequencing mechanisms and (b) meaning–form mappings to derive syntactic representations. The model is able to account for most of what is known about structural priming in adult speakers, as well as key findings in preferential looking and elicited production studies of language acquisition. The model suggests how abstract knowledge and concrete experience are balanced in the development and use of syntax.

Two striking contrasts currently exist in the sentence processing literature. First, whereas adult readers rely heavily on lexical information in the generation of syntactic alternatives, adult listeners in world-situated eye-gaze studies appear to allow referential evidence to override strong countervailing lexical biases (Tanenhaus, Spivey-Knowlton, Eberhard, & Sedivy, 1995). Second, in contrast to adults, children in similar listening studies fail to use this referential information and appear to rely exclusively on verb biases or perhaps syntactically based parsing principles (Trueswell, Sekerina, Hill, & Logrip, 1999). We explore these contrasts by fully crossing verb bias and referential manipulations in a study using the eye-gaze listening technique with adults (Experiment 1) and Wve-year-olds (Experiment 2). Results indicate that adults combine lexical and referential information to determine syntactic choice. Children rely A portion of this work was presented in proceedings to the 23rd Annual Conference of the Cognitive Science Society. The ideas in this paper owe much to our conversations with Lila Gleitman and to the comments of the many audiences who heard preliminary reports of this research. We thank Kirsten Thorpe for her assistance with testing, coding, and participant recruitment and Sylvia Yuan for her assistance in data analysis. We also gratefully acknowledge Tracy Dardick who carried out the norming studies and Jared Novick and David January who assisted in comparisons between head-mounted eye-tracking and our procedure. This work was supported by NIH Grant 1-R01-HD37507 to the second author and a National Science Foundation Science and Technology grant to the Institute for Research in Cognitive Science at the University of Pennsylvania (NSF-STC Coo...

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Cross-linguistic similarities and differences in early lexical and grammatical development are reported for 1001 English-speaking children and 386 Italian-speaking children between 1;6 and 2;6. Parents completed the English or Italian versions of the MacArthur Communicative Development Inventory: Words and Sentences, a parent report instrument that provides information about vocabulary size, vocabulary composition and grammatical complexity across this age range. The onset and subsequent growth of nouns, predicates, function words and social terms proved to be quite similar in both languages. No support was found for the prediction that verbs would emerge earlier in Italian, although Italians did produce a higher proportion of social terms, and there were small but intriguing differences in the shape of the growth curve for grammatical function words. A strikingly similar nonlinear relationship between grammatical complexity and vocabulary size was observed in both languages, and examination of the order in which function words are acquired also yielded more similarities than differences. However, a comparison of the longest sentences reported for a subset of children demonstrates large cross-linguistic differences in the

Various lines of research on language have converged on the premise that linguistic knowledge has as its basic unit pairings of form and meaning. The precise nature of the meanings involved, however, remains subject to the longstanding debate between proponents of arbitrary, abstract representations and those who argue for more detailed perceptuo-motor representations. We propose a model, Embodied Construction Grammar (ECG), which integrates these two positions by casting meanings as schematic representations embodied in human perceptual and motor systems. On this view, understanding everyday language entails running mental simulations of its perceptual and motor content. Linguistic meanings are parameterizations of aspects of such simulations; they thus serve as an interface between the relatively discrete properties of language and the detailed and encyclopedic knowledge needed for simulation. This paper assembles evidence from neural imaging and psycholinguistic experiments supporting this general approach to language understanding. It also introduces ECG as a model that fulfills the requisite constraints, and presents two kinds of support for the model. First, we describe two verbal matching studies that test predictions the model makes about the degree of motor detail available in lexical representations. Second, we demonstrate the viability and utility of ECG as a grammar formalism through its capacity to support computational models of language understanding and acquisition.

A basis for generating expectancies for verbs from nouns The role of expectancy generation in sentence processing has attracted increased attention over the past several years. There has long been reason to believe that comprehenders generate expectations about upcoming words as they process sentences presented incrementally (Kutas & Hillyard, 1984; Marslen-Wilson & Welsh, 1978), and computational modeling suggests that implicit expectancy generation can lead to the discovery of underlying syntactic structure (Elman, 1990). More recently, a number of researchers have suggested that although language understanding is clearly about more than simply anticipating what comes next, expectation does appear to play a critical