In this paper we explore a new theory of discourse structure that stresses the role of purpose and processing in discourse. In this theory, discourse structure is composed of three separate but interre-lated components: the structure of the sequence of utterances (called the linguistic structure), a struc-ture of purposes (called the intentional structure), and the state of focus of attention (called the attentional state). The linguistic structure consists of segments of the discourse into which the utter-ances naturally aggregate. The intentional structure captures the discourse-relevant purposes, expressed in each of the linguistic segments as well as relationships among them. The attentional state is an abstraction of the focus of attention of the participants as the discourse unfolds. The attentional state, being dynamic, records the objects, properties, and relations that are salient at each point of the discourse. The distinction among these components is essential to provide an adequate explanation of such discourse phenomena as cue phrases, referring expressions, and interruptions. The theory of attention, intention, and aggregation of utterances is illustrated in the paper with a number of example discourses. Various properties of discourse are described, and explanations for the behavior of cue phrases, referring expressions, and interruptions are explored. This theory provides a framework for describing the processing of utterances in a discourse. Discourse processing requires recognizing how the utterances of the discourse aggregate into segments, recognizing the intentions expressed in the discourse and the relationships among intentions, and track-ing the discourse through the operation of the mechanisms associated with attentional state. This processing description specifies in these recognition tasks the role of information from the discourse and from the participants ' knowledge of the domain. 1

This paper concerns relationships among focus of attention, choice of referring expression, and perceived coherence of utterances within a discourse segment. It presents a framework and initial theory of centering intended to model the local component of attentional state. The paper examines interactions between local coherence and choice of referring expressions; it argues that differences in coherence correspond in part to the inference demands made by different types of referring expressions, given a particular attentional state. It demonstrates that the attentional state properties modeled by centering can account for these differences

An agent's ability to understand an utterance depends upon its ability to relate that utterance to the preceding discourse. The agent must determine whether the utterance begins a new segment of the discourse, completes the current segment, or contributes to it. The intentional structure of the discourse, comprised of discourse segment purposes and their interrelationships, plays a central role in this process (Grosz and Sidner, 1986). In this thesis, we provide a computational model for recognizing intentional structure and utilizing it in discourse processing. The model specifies how an agent's beliefs about the intentions underlying a discourse affects and are affected by its subsequent discourse. We characterize this process for both interpretation and generation and then provide specific algorithms for modeling the interpretation process. The collaborative planning framework of SharedPlans (Lochbaum, Grosz, and Sidner, 1990; Grosz and Kraus, 1993) provides the basis for our model ...

Abstract. The ability to communicate is one of the salient properties of agents. Although a number of agent communication languages (ACLs) have been developed, obtaining a suitable formal semantics for ACLs remains one of the greatest challenges of multiagent systems theory. Previous semantics have largely been mentalistic in their orientation and are based solely on the beliefs and intentions of the participating agents. Such semantics are not suitable for most multiagent applications, which involve autonomous and heterogeneous agents, whose beliefs and intentions cannot be uniformly determined. Accordingly, we present a social semantics for ACLs that gives primacy to the interactions among the agents. Our semantics is based on social commitments and is developed in temporal logic. This semantics, because of its public orientation, is essential to providing a rigorous basis for multiagent protocols. 1

... This paper describes the IREPS system, emphasizing its dynamic construction of the task-related plan motivating the information-seeker's queries and the application of this component of a user model to handling utterances that violate the pragmatic rules of the system's world model. By reasoning on a model of the user's plans and goals, the system often can deduce the intended meaning of faulty utterances and allow the dialogue to continue without interruption. Some limitations of current plan inference systems are discussed. It is suggested that the problem of detecting and recovering from discrepancies between the system's model of the user's plan and the actual plan under construction by the user requires an enriched model that differentiates among its components on the basis of the support the system accords each component as a correct and intended part of the user's plan.

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This paper introduces the special issue of Knowledge-Based Systems on HumanComputer Collaboration (HCC). It derives a set of fundamental issues from a definition of collaboration, introduces two major approaches to HCC, and surveys each approach, showing how it formulates and addresses the issues. It concludes by proposing some themes that should characterize a unified approach to human-computer collaboration. 1 Introduction Collaboration is a process in which two or more agents work together to achieve shared goals. Thirty researchers came together in Raleigh, North Carolina in October of 1993 for a AAAI Fall Symposium dedicated to this topic. The goal of the symposium was to achieve a better understanding of Human-Computer Collaboration (HCC), collaboration involving at least one human and one computational agent. In particular, the symposium sought to explore the fundamental nature of collaborative problem solving, understand the constraints brought to bear by the differing charac...

Speech act theory is important not only in Linguistics, but also in Computer Science. It has applications in Distributed Computing, Distributed Artificial Intelligence, Natural Language Processing, and Electronic Data Interchange protocols. While much research into speech acts has been done, one aspect of them that has largely been ignored is their semantics, i.e., their conditions of satisfaction. A formal semantics for speech acts is motivated and presented here that relates their satisfaction to the intentions, know-how, and actions of the participating agents. This makes it possible to state several potentially useful constraints on communication and provides a basis for checking their consistency. An earlier version of this paper was presented at the Second Meeting on the Mathematics of Language, Tarrytown, NY, May 1991. Some parts of this paper overlap with [23]. y This research was supported by the National Science Foundation (through grant # IRI-8945845 to the Center for Co...

Agents in multiagent systems interact to a large extent by communicating. Such communication may be fruitfully studied from the point of view of speech act theory. In order for multiagent systems to be formally and rigorously designed and analyzed, a semantics of speech acts that gives their objective modeltheoretic conditions of satisfaction is needed. However, most research into multiagent systems that deals with communication provides only informal descriptions of the different message types used. And this problem is not addressed at all by traditional speech act theory or by AI research into discourse understanding. I provide a formal semantics for the major kinds of speech acts at a level that has not been considered before. The resulting theory applies uniformly to a wide range of multiagent systems. Some applications of this theory are outlined, and some of its theorems listed. 1

The central problem for pragmatics is that sentence meaning vastly underdetermines speaker’s meaning. The goal of pragmatics is to explain how the gap between sentence meaning and speaker’s meaning is bridged. This paper defends the broadly Gricean view that pragmatic interpretation is ultimately an exercise in mind-reading, involving the inferential attribution of intentions. We argue, however, that the interpretation process does not simply consist in applying general mind-reading abilities to a particular (communicative) domain. Rather, it involves a dedicated comprehension module, with its own special principles and mechanisms. We show how such a metacommunicative module might have evolved, and what principles and mechanisms it might contain.