’s glue logic for computing logical form dynamic. This allows us to model a dialogue agent’s understanding of what the update of the semantic representation of the dialogue would be after his next contribution, including the effects of the rhetorical moves that he is contemplating performing next. This is a pre-requisite for developing a model of how agents reason about what to say next. We make the glue logic dynamic by using a dynamic public announcement logic ( pal ). We (...) extend pal with a particular variety of default reasoning suited to reasoning about discourse—this default reasoning being an essential component of inferring the pragmatic effects of one’s dialogue moves. We add to the pal language a new type of announcement, known as ceteris paribus announcement, and this is used to model how an agent anticipates the (default) pragmatic effects of his next dialogue move. Our extended pal validates certain intuitive patterns of default inference that existing pal s for practical reasoning do not. We prove that the dynamic glue logic has a pspace validity problem, and as such is no more complex than pal with multiple $${\square}$$ operators. (shrink)

I show how a conversational process that takes simple, intuitively meaningful steps may be understood as a sophisticated computation that derives the richly detailed, complex representations implicit in our knowledge of language. To develop the account, I argue that natural language is structured in a way that lets us formalize grammatical knowledge precisely in terms of rich primitives of interpretation. Primitives of interpretation can be correctly viewed intentionally, as explanations of our choices of linguistic actions; the model therefore fits our (...) intuitions about meaning in conversation. Nevertheless, interpretations for complex utterances can be built from these primitives by simple operations of grammatical derivation. In bridging analyses of meaning at semantic and symbol‐processing levels, this account underscores the fundamental place for computation in the cognitive science of language use. (shrink)

This paper presents a dual intention model (DIM) of demonstrations as actions to show the agentive nature of demonstrations. According to the DIM, demonstrations are complex actions that contain as components at least three elements: an abductive intention, a deictic intention, and a basic ostensive act of indication. This paper unpacks these three components and discusses their roles from the viewpoint of the philosophy of action and the philosophy of language. It also shows how the DIM applies in selected practical (...) examples and explains the merits of the model in the context of other views on demonstrations and demonstratives. (shrink)

Acknowledgements Five out of the 13 contributions to this volume originate from papers which were presented at the international workshop on “Epistemology, Context, Formalism” held at the MSH-Lorraine in Nancy, France, on November the ...

An essential ingredient of language use is our ability to reason about utterances as intentional actions. Linguistic representations are the natural substrate for such reasoning, and models from computational semantics can often be seen as providing an infrastructure to carry out such inferences from rich and accurate grammatical descriptions. Exploring such inferences offers a productive pragmatic perspective on problems of interpretation, and promises to leverage semantic representations in more flexible and more general tools that compute with meaning.

We relate the theory of presupposition accommodation to a computational framework for reasoning in conversation. We understand presuppositions as private commitments the speaker makes in using an utterance but expects the listener to recognize based on mutual information. On this understanding, the conversation can move forward not just through the positive effects of interlocutors’ utterances but also from the retrospective insight interlocutors gain about one anothers’ mental states from observing what they do. Our title, ENLIGHTENED UPDATE, highlights such cases. Our (...) approach fleshes out two key principles: that interpretation is a form of intention recognition; and that intentions are complex informational structures, which specify commitments to conditions and to outcomes as well as to actions. We present a formalization and implementation of these principles for a simple conversational agent, and draw on this case study to argue that pragmatic reasoning is holistic in character, continuous with common-sense reasoning about collaborative activities, and most effectively characterized by associating specific, reliable interpretive constraints directly with grammatical forms. In showing how to make such claims precise and to develop theories that respect them, we illustrate the general place of computation in the cognitive science of language. (shrink)

We use a dynamic, context-sensitive approach to abductive interpretation to describe coordinated processes of understanding, generation and accommodation in dialogue. The agent updates the dialogue uniformly for its own and its interlocutors’ utterances, by accommodating a new context, inferred abductively, in which utterance content is both true and prominent. The generator plans natural and comprehensible utterances by exploiting the same abductive preferences used in understanding. We illustrate our approach by formalizing and implementing some interactions between information structure and the form (...) of referring expressions. (shrink)