This chapter describes Conversational Agents (CAs) in the context of Systems Engineering. A CA is a computer program which interacts with a user through natural language dialogue and provides some form of service. CA technology has two points of interest to systems engineers: the use of systems engineering techniques in CA research and the application of CAs in project development. CAs offer the opportunity to automate more complex applications than are feasible with conventional web interfaces. Currently such applications require a human expert in the domain to mediate between the user and the application. The CA effectively replaces the human expert. This chapter reviews the current capabilities of various CA technologies, outlines a development methodology for systems engineering practitioners interested in developing real world applications and suggests a number of directions for systems engineers who wish to participate in CA research.

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Systems Engineering and Conversational Agents

Problem statement: Feature selection is a task of crucial importance for the application of
machine learning in various domains. In addition, the recent increase of data dimensionality poses a
severe challenge to many existing feature selection approaches with respect to efficiency and
effectiveness. As an example, genetic algorithm is an effective search algorithm that lends itself
directly to feature selection; however this direct application is hindered by the recent increase of data
dimensionality. Therefore adapting genetic algorithm to cope with the high dimensionality of the data
becomes increasingly appealing. Approach: In this study, we proposed an adapted version of genetic
algorithm that can be applied for feature selection in high dimensional data. The proposed approach is
based essentially on a variable length representation scheme and a set of modified and proposed
genetic operators. To assess the effectiveness of the proposed approach, we applied it for cues phrase
selection and compared its performance with a number of ranking approaches which are always
applied for this task. Results and Conclusion: The results provide experimental evidences on the
effectiveness of the proposed approach for feature selection in high dimensional data.

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Feature selection for high dimensional data: An evolutionary filter approach.

This paper is about INES, an intelligent, multimodal tutoring environment, and how we build a tutor agent in the environment that tries to be sensitive to the mental state of the student that interacts with it. The environment was primarily designed to help students practice nursing tasks. For example, one of the implemented tasks is to give a virtual patient a subcutaneous injection. The students can interact multimodally using speech and a haptic device under the guidance of the virtual embodied tutor. INES takes into account elements of the student’s character and an appraisal of the student’s actions to estimate the mental state of the student. This information is used to plan and execute the actions and responses of the tutor agent.

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Affect in tutoring dialogues

Emotions and personality have received quite a lot of attention the last few years in research on embodied conversational agents. Attention is also increasingly being paid to matters of social psychology and interpersonal aspects, for work of our group). Given the nature of an embodied conversational agent�s main activity: 'conversation', we feel that interpersonal issues should be central in their design. We consider the case of tutoring systems in more depth and examine some of the interpersonal factors that need to be accounted for when building emotionally intelligent tutors.

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Socially Intelligent Tutor Agents

This chapter addresses the challenge of building or authoring an Intelligent Tutoring System (ITS), along with the problems that have arisen and been dealt with, and the solutions that have been tested. We begin by clarifying what building an ITS entails, and then position today’s systems in the overall historical context of ITS research. The chapter concludes with a series of open questions and an introduction to the other chapters in this part of the book.

Building Intelligent Tutoring Systems: An Overview

We developed a generic teaching environment that uses agents to support learning. An agent platform developed in our research group is used. The system is generic in the sense that the cognition core (domain model, student model and instruction model) is separated from the exercise modules and user interfaces. The architecture allows different user interfaces. An application of the environment for nurse training has been implemented.

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Developing a generic agent-based intelligent tutoring system

SCHISMA is a joint research project of KPN (Royal PTT Nederland) and the University of Twente. The
project aims at providing a natural language dialogue system which interfaces a database containing
information about theatre performances in a certain city or region. The interface should make it possible
to ask about performances in general, to tune in to a specific performance and, if desired, make a
reservation for this performance. Research until now has concentrated on various aspects of realising
such a theatre information and booking system. Among these aspects are the building of a Wizard of Oz
environment for the acquisition of a corpus of dialogues for this domain, analysis and tagging of the
dialogue corpus, recognition of domain-specific concepts (actors, authors, plays, dates, etc.), syntactic
analysis and dialogue modelling. The emphasis in this paper will be on the analysis of individual
utterances at various levels. Most important for the project are short and medium term goals of delivering
prototype systems that allow demonstration of the system and evaluation of the design choices. Due to
these goals the project does not strive at incorporating advanced but isolated research results on discourse
models and syntactic and semantic analysis. Rather we investigate how to identify user preferences and
how to embed systems like these in a more comprehensive environment of information and transaction
services.

R. op den Akker

Papers

Developing a generic agent-based intelligent tutoring system

Language analysis for dialogue management in a theatre information and booking system