In contrast to expectation-based, predictive views of discourse comprehension, a model is developed in which the initial processing is strictly bottom-up. Word meanings are activated, propositions are formed, and inferences and elaborations are produced without regard to the discourse context. However, a network of interrelated items is created in this manner, which can be integrated into a coherent structure through a spreading activation process. Data concerning the time course of word identification in a discourse context are examined. A simulation of arithmetic word-problem under-standing provides a plausible account for some well-known phenomena in this area. Discourse comprehension, from the viewpoint of a computa-tional theory, involves constructing a representation of a dis-course upon which various computations can be performed, the outcomes of which are commonly taken as evidence for com-prehension. Thus, after comprehending a text, one might rea-sonably expect to be able to answer questions about it, recall or summarize it, verify statements about it, paraphrase it, and SO on.

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The paper surveys work on the computational modeling of the origins and evolution of language. The main approaches are clarified and some example experiments from the domains of the evolution of communication, phonetics, lexicon formation, and syntax are discussed. 1 Introduction The paper surveys research in which software simulations and experiments with robotic agents are used to explore the viewpoint that language is a complex dynamical system. The main goal of the paper is to outline the approaches and show example experiments. Much more work needs to be done to arrive at a full-fledged theory of the origins of language and even about the work already done much more can be said than is possible in a single paper. Nevertheless, I hope to show that a new exciting approach to the study of the origins and evolution of language is taking shape. The rest of the paper is in four parts. The next section clarifies the notion of a complex system and the multi-agent perspective. Section 3...

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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, ...

MacWhinney (1978) presented a computational model of the acquisition of morphophonology. The present chapter attempts to extend the model presented in that earlier paper to the acquisition of word-order patterns. This extension is supported by an examination of the previous research on syntactic acquisition. In the final section of the chapter, further possible extensions to phonology and semantics are considered. The crucial claim underlying the basic approach to both morphophonology and syntax is that use of a given rule system is governed by a system of alternative strategies. Within such a multileveled model, alternative strategies can be compared in terms of their relative complexity. In the present chapter, these alternative strategies are evaluated through application of the following analytic technique: 1. A relatively simple strategy that can account for at least some of the observed data is presented. 2. It is shown that there are at least some data that are best explained by this strategy. 3. It is shown that, at some point in development, the child produces forms that cannot be explained by this simple strategy alone. 4. A strategy of somewhat greater complexity and power is introduced and it is shown that this strategy can account for at least some of the data not explained by the simpler (and weaker) strategy. This line of argumentation proceeds until evidence has been presented for six alternative strategies in word-order processing.

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foundations of standard approaches to language studies involve an incoherence in their presuppositions. Second, we present an alternative approach that resolves this incoherence. Third, we discuss how this error manifests itself in categorial grammars and model theoretic possible worlds semantics. Fourth, we suggest some possible revisions in standard approaches to accommodate them to the alternative that we suggest. We arrive at a fundamentally functional, or pragmatic, conception - an interactive conception - of the nature of language and meaning. Contents 1.

this document are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Office of Scientific Reses.ch of the U.S. Government. t am very grateful to William Mann for many helpful comments on various versions of this !3aer; much of the discussion builds on work by him. l am also deeply indebted to Michael A.K. Hallida'; I have 13rofited from and drawn heavily on his insights about English grammar and semantics and the systemic framework. I am solely responsible for all errors

We describe a system of thematic roles and frames designed to address a number of problems in semantic representations at the lexical semantic level. Our primary objective is broad expressiveness, so that real domains can practically be encoded. However, for both empirical and computational reasons we limit the number of role types to four, allocating this structure to the strongest associations. We show how the system incorporates imageschematic semantics to encode various schematization operations relating to scales and reification. Keywords: semantics, cognitive modelling 1 Introduction Anyone attempting to build a natural language processing model for any application beyond syntactic parsing faces a dilemma in choosing a meaning representation. On the one hand, traditional knowledge representation languages such as predicate logic, frames, or semantic networks permit arbitrary flexibility in choosing the predicates or types. This makes it difficult to compare or falsify theories...