this paper, is when two participants can both communicate with each other and observe each other's actions on some shared artifact

this paper. MISQ Review articles survey, conceptualize, and synthesize prior MIS research and set directions for future research. For more details see http://www.misq.org/misreview/announce.html The associated web site for this paper is located at http://misq.org/misreview/teeni.shtml communication to a view that assesses the balance between medium and message form. There is also a need to look more closely at the process of communication in order to identify more precisely any potential areas of computer support

Abstract. In this paper, we address the problem of providing guidelines to designers of mixed-initiative artificial intelligence systems, which specify when the system should take the initiative to solicit further input from the user, in order to carry out a problem solving task. We first present a utility-based quantitative framework which is dependent on modeling: whether the user has the knowledge the system is seeking, whether the user is willing to provide that knowledge and whether the user would be capable of understanding the request for information from the system. Examples from the application of sports scheduling are included. We also discuss a qualitative version of the model, for applications with sparse data. This paper demonstrates a novel use for user models, one in which the system does not simply alter its generation based on the user model, but in fact makes a user-specific decision about whether to interact at all.

This paper describes a plan-based agent architecture for modeling NL cooperative dialogue; in particular, the paper focuses on the interpretation dialogue and explanation of its coherence by means of the recognition of the speakers' underlying intentions. The approach we propose makes it possible to analyze and explain in a uniform way several apparently unrelated linguistic phenomena, which have been often studied separately and treated via ad-hoc methods in the models of dialogue presented in the literature. Our model of linguistic interaction is based on the idea that dialogue can be seen as any other interaction among agents: therefore, domain-level and linguistic actions are treated in a similar way. Our agent architecture is based on a two-level representation of the knowledge about acting: at the metalevel, the Agent Modeling plans describe the recipes for plan formation and execution (they are a declarative representation of a reactive planner); at the object level, the domain ...

Intelligent Systems are served by Intelligent User Interfaces aimed to improve the efficiency, effectiveness and adaptation of the interaction between the user and the computer by representing, understanding and implementing models. The Intelligent User Interface Model (IUIM) helps to design and develop Intelligent Systems considering its architecture and its behavior. It focuses the Interaction and Dialogue between User and System at the heart of an Intelligent Interactive System. An architectural model, which defines the components of the model, and a conceptual model, which relates to its contents and behavior, compose the IUIM. The conceptual model defines three elements: an Adaptive User Model (including components for building and updating the user model), a Task Model (including general and domain specific knowledge) and an Adaptive Discourse Model (to be assisted by an intelligent help and a learning module). We will show the implementation of the model by describing an application named Stigma- A STereotypical Intelligent General Matching Agent for Improving Search Results on the Internet. Finally, we compared the new model with others, stating the differences and the advantages of the proposed model.

This paper describes a framework for the representation and interpretation of indirect speech acts, relating them to the politeness phenomenon, with particular attention to the case of requests. The speech acts are represented as actions of a plan library and are activated on the basis of the presence of syntactic and semantic information in the linguistic form of the input utterance. The speech act analyzer receives in input the semantic representation of the input sentence and uses the politeness indicators to climb up the decomposition and generalization hierarchies of acts encoded in the library. During this process, it eliminates the indicators and collects the negated presuppositions (represented as effects of the indirect speech act) that characterize the politeness forms. Some cyclic paths in the hierarchy allow the system to cope with complex sentences including nested politeness indicators. In the proper places of the hierarchy the semantic representation of the input sentenc...

We examine clarification dialogue, a mechanism for refining user questions with follow-up questions, in the context of open domain Question Answering systems. We develop an algorithm for clarification dialogue recognition through the analysis of collected data on clarification dialogues and examine the importance of clarification dialogue recognition for question answering. The algorithm is evaluated and shown to successfully recognize the occurrence of clarification dialogue in the majority of cases and to simplify the task of answer retrieval.

mwflemin,rcohen¡ In this paper, we present a utility-based decision making process to be used by a system in determining when to take the initiative to interact with a user, in a mixed-initiative artificial intelligence system. The decision making is based on a calculation of the expected utility of various courses of action and the likelihood that the user will be an effective contributor of information, if an interaction were initiated. We demonstrate the model in the application of sports scheduling, but discuss its potential for other applications as well. In particular, we contrast with existing work on utility-based reasoning in environments of agent-agent interaction. Our overall conclusion is that there is value to adopting an explicit reasoning process about taking the initiative as part of the overall deliberation about problem solving in collaborative environments. 1

this paper, we present two different models for plan recognition - one based on Kautz's algorithms, which employs fault critiquing in order to determine whether plan ambiguity must be resolved, and one based on Carberry's context model system, which integrates specific accessing of user models to constrain the processing. We highlight the contribution of user models in each case. We then present an example where both kinds of user model integrations are beneficial. We conclude with some speculation for future work, indicating how our distinct approaches may find some common ground.

. In this paper we outline a model for plan recognition in advice-giving settings which incorporates user modeling techniques and we show how to extend it to allow a wider range of user feedback than in previous plan recognition models. In particular, we discuss how this model allows for clarification dialogues both in cases where there are faults in a user's plan and in cases where alternate decompositions of plans might be selected as the basis for a user-specific response. We also describe an extension of the model which allows more general descriptions of the plans being recognized to be presented to users, due to the inclusion of certain generalized action nodes in the plan library. Since the user is then able to take the initiative to request a more specific response from the system, there is an additional opportunity for user feedback. We conclude with some reasons why these extensions for user feedback are valuable and discuss some potential new directions for plan recognition ...