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UMUAI Tables of Contents: 01020304050607080910111213141516171819

User Modeling and User-Adapted Interaction 9

Editors:Alfred Kobsa
Standard No:ISSN 0924-1868 (print) EISSN 1573-1391 (online)
Links:link.springer.com | Table of Contents
  1. UMUAI 1999-04 Volume 9 Issue 1/2
  2. UMUAI 1999-09 Volume 9 Issue 3
  3. UMUAI 1999 Volume 9 Issue 4

UMUAI 1999-04 Volume 9 Issue 1/2

Lifelike Pedagogical Agents for Mixed-initiative Problem Solving in Constructivist Learning Environments BIBAKFull-Text 1-44
  James C. Lester; Brian A. Stone
Mixed-initiative problem solving lies at the heart of knowledge- based learning environments. While learners are actively engaged in problem-solving activities, learning environments should monitor their progress and provide them with feedback in a manner that contributes to achieving the twin goals of learning effectiveness and learning efficiency. Mixed-initiative interactions are particularly critical for constructivist learning environments in which learners participate in active problem solving. We have recently begun to see the emergence of believable agents with lifelike qualities. Featured prominently in constructivist learning environments, lifelike pedagogical agents could couple key feedback functionalities with a strong visual presence by observing learners' progress and providing them with visually contextualized advice during mixed-initiative problem solving. For the past three years, we have been engaged in a large-scale research program on lifelike pedagogical agents and their role in constructivist learning environments. In the resulting computational framework, lifelike pedagogical agents are specified by
  • (1) a behavior space containing animated and vocal behaviors,
  • (2) a design-centered context model that maintains constructivist problem
        representations, multimodal advisory contexts, and evolving
        problem-solving tasks, and
  • (3) a behavior sequencing engine that in realtime dynamically selects and
        assembles agents' actions to create pedagogically effective, lifelike
        behaviors. To empirically investigate this framework, it has been instantiated in a full-scale implementation of a lifelike pedagogical agent for Design-A-Plant, a learning environment developed for the domain of botanical anatomy and physiology for middle school students. Experience with focus group studies conducted with middle school students interacting with the implemented agent suggests that lifelike pedagogical agents hold much promise for mixed-initiative learning.
    Keywords: Lifelike agents; pedagogical agents; animated agents; knowledge-based learning environments; mixed-initiative interaction; intelligent tutoring systems; intelligent multimedia presentation; intelligent interfaces; task models
  • Mixed-Initiative Issues in an Agent-Based Meeting Scheduler BIBAKFull-Text 45-78
      Amedeo Cesta; Daniela D'Aloisi
    This paper concerns mixed-initiative interaction between users and agents. After classifying agents according to their task and their interactivity with the user, the critical aspects of delegation-based interaction are outlined. Then MASMA, an agent system for distributed meeting scheduling, is described, and the solutions developed to control interaction are explained in detail. The issues addressed concern: the agent capability of adapting its behavior to the user it is supporting; the solution adopted to control the shift of initiative between personal agents, their users and other agents in the environment; the availability of features, e.g. the inspection mechanism, that endow the user with a further level of control to enhance his sense of trust in the agent.
    Keywords: personal assistants; mixed-initiative interaction; multi-agent systems; human computer interaction
    Exploring Mixed-Initiative Dialogue Using Computer Dialogue Simulation BIBAKFull-Text 79-91
      Masato Ishizaki; Matthew Crocker
    This paper experimentally shows that mixed-initiative dialogue is not always more efficient than non-mixed initiative dialogue in route finding tasks. Based on the dialogue model proposed in Conversation Analysis and Discourse Analysis à la the Birmingham school and Whittaker and Stenton's definition of initiative, we implement dialogue systems and obtain experimental results by making the systems interact with each other. Across a variety of instantiations of the dialogue model, the results show that with easy problems, the efficiency of mixed-initiative dialogue is a little better than or equal to that of non-mixed-initiative dialogue, while with difficult problems mixed-initiative dialogue is less efficient than non-mixed-initiative dialogue.
    Keywords: mixed-initiative dialogue; computer dialogue simulation; efficiency of dialogue; discourse analysis; task-oriented dialogue
    A Computational Mechanism for Initiative in Answer Generation BIBAKFull-Text 93-132
      Nancy Green; Sandra Carberry
    Initiative in dialogue can be regarded as the speaker taking the opportunity to contribute more information than was his obligation in a particular discourse turn. This paper describes the use of stimulus conditions as a computational mechanism for taking the initiative to provide unrequested information in responses to Yes-No questions, as part of a system for generating answers to Yes-No questions. Stimulus conditions represent types of discourse contexts in which a speaker is motivated to add unrequested information to his answer. Stimulus conditions may be triggered not only by the discourse context at the time when the question was asked, but also by the anticipated context resulting from providing part of the response. We define a set of stimulus conditions based upon previous linguistic studies and a corpus analysis, and describe how evaluation of these stimulus conditions makes use of information from a User Model. Also, we show how the stimulus conditions are used by the generation component of the system. An evaluation was conducted of the implemented system. The results indicate that the responses generated by our system containing extra information provided on the basis of this initiative mechanism are viewed more favorably by users than responses without the extra information.
    Keywords: natural language dialogue; discourse initiative
    User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues BIBAKFull-Text 133-166
      Adelheit Stein; Jon Atle Gulla; Ulrich Thiel
    Intelligent dialogue systems usually concentrate on user support at the level of the domain of discourse, following a plan-based approach. Whereas this is appropriate for collaborative planning tasks, the situation in interactive information retrieval systems is quite different: there is no inherent plan-goal hierarchy, and users are known to often opportunistically change their goals and strategies during and through interaction. We need to allow for mixed-initiative retrieval dialogues, where the system evaluates the user's individual dialogue behavior and performs situation-dependent interpretation of user goals, to determine when to take the initiative and to change the control of the dialogue, e.g., to propose (new) problem-solving strategies to the user. In this article, we present the dialogue planning component of a concept- oriented, logic-based retrieval system (MIRACLE). Users are guided through the global stages of the retrieval interaction but may depart, at any time, from this guidance and change the direction of the dialogue. When users submit ambiguous queries or enter unexpected dialogue control acts, abductive reasoning is used to generate interpretations of these user inputs in light of the dialogue history and other internal knowledge sources. Based on these interpretations, the system initiates a short dialogue offering the user suitable options and strategies for proceeding with the retrieval dialogue. Depending on the user's choice and constraints resulting from the history, the system adapts its strategy accordingly.
    Keywords: Conversational retrieval; mixed initiative; dialogue planning; dialogue act interpretation; abduction
    An Approach to Mixed Initiative Spoken Information Retrieval Dialogue BIBAKFull-Text 167-213
      Eli Hagen
    We present an approach to mixed initiative dialogue in acoustic user interfaces to databases. First, we discuss how we distinguish between initiative and control in mixed initiative information retrieval dialogue and how the notions of taking, keeping, and relinquishing initiative and control are reflected in our approach. Based on this discussion, we develop a dialogue planning algorithm. This algorithm distinguished between resources and routines and between the type and the content of an utterance; type and content are calculated separately by routines that reason on the resources -- a dialogue model, a dialogue history, and an application description. Through this division we achieve a dialogue where the system adapts to the user's attempts at changing the direction of a dialogue. Finally, we argue that automatic segmentation of the dialogue and automatic tracking of initiative and control is inherent to our approach.
    Keywords: dialogue management; dialogue planning; mixed initiative dialogue; spoken dialogue systems

    UMUAI 1999-09 Volume 9 Issue 3

    Logic-Based Representation and Reasoning for User Modeling Shell Systems BIBAKFull-Text 217-282
      Wolfgang Pohl
    Core services of user modeling shell systems include the provision of representations for user model contents and for other relevant knowledge, and of reasoning mechanisms. These representation and reasoning facilities should be powerful and flexible, in order to satisfy both complex and specialized needs that developers of user modeling systems may have. This article first identifies these needs through a comprehensive overview of logic-based representation and reasoning in user modeling system. Then, the AsTRa (Assumption Type Representation) framework for logic-based user model representation and reasoning is presented. This framework obtains its power and flexibility through an integration of the two main scientific approaches that were pursued to date, namely the partition approach and the modal logic approach. The central notion of the framework is the 'assumption type', a partition-like partial knowledge base for storing all assumptions about the user that are of the same type. Within assumption types, logic-based representation formalisms can be employed. The semantics of assumption types and content formalisms can be characterized in terms of modal logic, so that an extension to full modal logic is possible. Moreover, special mechanisms for handling so-called 'negative assumptions' are developed, which are also firmly grounded in modal logic semantics. The paper concludes with a description of the user modeling shell BGP-MS as a prototypical implementation of AsTRa, and a discussion of the approach in the light of other user modeling shells.
    Keywords: modal logic approach; partition approach; user model representation and reasoning; user modeling shell systems
    Erratum BIBFull-Text 283

    UMUAI 1999 Volume 9 Issue 4

    A Fuzzy-Based Approach to Stereotype Selection in Hypermedia BIBAKFull-Text 285-320
      Luigi Di Lascio; Enrico Fischetti
    This paper presents a stereotype-based user model for adaptive hypermedia systems. We use a suitable algebraic fuzzy structure which can adequately reflect some features of the user in the model, and apply this model to adapt the navigation and the content of hypermedia nodes to the user's needs. The model includes temporal representations of the user and approximates every real user by a set of stereotypes, from which the one realizing the best approximation can always be extracted. The set of stereotypes is the support set of the structure and the operations defined therein may be supplied with adequate semantics which allow for the selection of the stereotype.
    Keywords: fuzzy sets; user modeling; adaptive hypermedia systems; stereotype selection
    Human Plausible Reasoning for Intelligent Help BIBAKFull-Text 321-375
      Maria Virvou; Benedict Du Boulay
    This paper is about providing intelligent help to users interacting with an operating system. Its main focus is an investigation of Human Plausible Reasoning Theory (Collins & Michalski, 1989) to infer the commands the user should have typed, given what they did type. The theory has been adapted and incorporated into a prototype Intelligent Help System (IHS) for UNIX users, called RESCUER, and has been used for the generation and evaluation of hypotheses about users' beliefs underlying the observed users' actions on the UNIX file store. The hypotheses generated by RESCUER were compared to those made by human experts on the sample scripts from UNIX user sessions. The potential for Human Plausible Reasoning as a mechanism to reason about slips and misconceptions is discussed.
    Keywords: user modelling; intelligent help systems; human plausible reasoning; error diagnosis; plan recognition