43,877 research outputs found

    Natural Language Dialogue Service for Appointment Scheduling Agents

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    Appointment scheduling is a problem faced daily by many individuals and organizations. Cooperating agent systems have been developed to partially automate this task. In order to extend the circle of participants as far as possible we advocate the use of natural language transmitted by e-mail. We describe COSMA, a fully implemented German language server for existing appointment scheduling agent systems. COSMA can cope with multiple dialogues in parallel, and accounts for differences in dialogue behaviour between human and machine agents. NL coverage of the sublanguage is achieved through both corpus-based grammar development and the use of message extraction techniques.Comment: 8 or 9 pages, LaTeX; uses aclap.sty, epsf.te

    Politeness and Alignment in Dialogues with a Virtual Guide

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    Language alignment is something that happens automatically in dialogues between human speakers. The ability to align is expected to increase the believability of virtual dialogue agents. In this paper we extend the notion of alignment to affective language use, describing a model for dynamically adapting the linguistic style of a virtual agent to the level of politeness and formality detected in the user’s utterances. The model has been implemented in the Virtual Guide, an embodied conversational agent giving directions in a virtual environment. Evaluation shows that our formality model needs improvement, but that the politeness tactics used by the Guide are mostly interpreted as intended, and that the alignment to the user’s language is noticeable

    Specification Techniques for Multi-Modal Dialogues in the U-Wish Project

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    In this paper we describe the development of a specification\ud technique for specifying interactive web-based services. We\ud wanted to design a language that can be a means of\ud communication between designers and developers of interactive services, that makes it easier to develop web-based services fitted to the users and that shortens the pathway from design to implementation. The language, still under development, is based on process algebra and can be\ud connected to the results of task analysis. We have been\ud working on the automatic generation of executable prototypes\ud out of the specifications. In this way the specification\ud language can establish a connection between users, design\ud and implementation. A first version of this language is\ud available as well as prototype tools for executing the specifications. Ideas will be given as to how to make the connection between specifications and task analysis

    Conversational Sensing

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    Recent developments in sensing technologies, mobile devices and context-aware user interfaces have made it possible to represent information fusion and situational awareness as a conversational process among actors - human and machine agents - at or near the tactical edges of a network. Motivated by use cases in the domain of security, policing and emergency response, this paper presents an approach to information collection, fusion and sense-making based on the use of natural language (NL) and controlled natural language (CNL) to support richer forms of human-machine interaction. The approach uses a conversational protocol to facilitate a flow of collaborative messages from NL to CNL and back again in support of interactions such as: turning eyewitness reports from human observers into actionable information (from both trained and untrained sources); fusing information from humans and physical sensors (with associated quality metadata); and assisting human analysts to make the best use of available sensing assets in an area of interest (governed by management and security policies). CNL is used as a common formal knowledge representation for both machine and human agents to support reasoning, semantic information fusion and generation of rationale for inferences, in ways that remain transparent to human users. Examples are provided of various alternative styles for user feedback, including NL, CNL and graphical feedback. A pilot experiment with human subjects shows that a prototype conversational agent is able to gather usable CNL information from untrained human subjects

    Analysis of Dialogical Argumentation via Finite State Machines

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    Dialogical argumentation is an important cognitive activity by which agents exchange arguments and counterarguments as part of some process such as discussion, debate, persuasion and negotiation. Whilst numerous formal systems have been proposed, there is a lack of frameworks for implementing and evaluating these proposals. First-order executable logic has been proposed as a general framework for specifying and analysing dialogical argumentation. In this paper, we investigate how we can implement systems for dialogical argumentation using propositional executable logic. Our approach is to present and evaluate an algorithm that generates a finite state machine that reflects a propositional executable logic specification for a dialogical argumentation together with an initial state. We also consider how the finite state machines can be analysed, with the minimax strategy being used as an illustration of the kinds of empirical analysis that can be undertaken.Comment: 10 page

    Presenting Arguments as Fictive Dialogue

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    Presentation of an argument can take many different forms ranging from a monologue to advanced graphics and diagrams. This paper investigates the presentation of one or more arguments in the form of a fictive dialogue. This technique was already employed by Plato, who used fictive conversations between Socrates and his contemporaries to put his arguments forward. Ever since, there have been influential authors – including Desiderius Erasmus, Sir Thomas More and Mark Twain – that have used dialogue in this way. In this paper, we define the notion of a fictive dialogue, motivate it is as a topic for investigation, and present a qualitative and quantitative study of five fictive dialogues by well-known authors. We conclude by indicating how our preliminary and ongoing investigations may inform the development of systems that automatically generate argumentative fictive dialogue

    Training an adaptive dialogue policy for interactive learning of visually grounded word meanings

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    We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor. The system integrates an incremental, semantic parsing/generation framework - Dynamic Syntax and Type Theory with Records (DS-TTR) - with a set of visual classifiers that are learned throughout the interaction and which ground the meaning representations that it produces. We use this system in interaction with a simulated human tutor to study the effects of different dialogue policies and capabilities on the accuracy of learned meanings, learning rates, and efforts/costs to the tutor. We show that the overall performance of the learning agent is affected by (1) who takes initiative in the dialogues; (2) the ability to express/use their confidence level about visual attributes; and (3) the ability to process elliptical and incrementally constructed dialogue turns. Ultimately, we train an adaptive dialogue policy which optimises the trade-off between classifier accuracy and tutoring costs.Comment: 11 pages, SIGDIAL 2016 Conferenc

    Proceedings of the 11th European Agent Systems Summer School Student Session

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    This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz
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