Auton Agent Multi-Agent Syst (2010) 20:1–2 DOI 10.1007/s10458-009-9098-5
Guest editorial of the special issue on intelligent virtual agents Stefan Kopp · Ruth Aylett · Jonathan Gratch · Patrick L. Olivier · Catherine Pelachaud
Published online: 19 May 2009 Springer Science+Business Media, LLC 2009
We are pleased to present this special issue on Intelligent Virtual Agents. Intelligent Virtual Agents (IVAs) are autonomous, graphically embodied agents in a dynamic social environment. They are capable of real-time perception, cognition and action, which allows to them interact autonomously and intelligently with the environment, other IVAs, and especially with human users. Research on IVAs now encompasses a wide range of disciplines; artificial intelligence, autonomous agents, robotics, cognitive and social psychology, linguistics and conversation models, affective computing, human-computer interaction, sociology and numerous application domains.This issue contains updated and extended versions of selected papers from last year’s IVA 08 conference, held in Tokyo. They represent the state of the art in the very interdisciplinary research that needs to be carried out to build IVAs. Ito et al. present a decision-theoretic framework for belief maintenance and decisionmaking. It is applied to the human capacity for self-deception, by modeling processes for determining a desired belief state, the biasing of internal beliefs towards this desired belief state, and the decision-making based upon the integrated biases. Si et al. employ a multi-agent decision-theoretic framework to computationally model the cognitive appraisal of events in the environment. Based on the agents’ recursive beliefs about self and others, emotional experience is linked to the interpretations of these events, which allows for simulating “real emotions” in virtual characters and for predicting the human user’s emotional experience. Becker & Wachsmuth introduce an approach to combine primary and secondary emotions to a coherent affective state and emotional expressions of a virtual agent. Primary emotions reflect the continuous progression of bodily feelings, while secondary emotions reflect the cognitive appraisal of events in the light of current experiences and expectations. An evaluation study in a card playing game scenario shows that the inclusion of secondary emotions affects the user’s impression of the agent. Moving into the modeling of interactional behavior, the paper by Lance & Marsella considers expressive gaze shifts as a signal to enhance the believability of a simulated character. Such gaze shifts can be performed in many different ways, each of which can potentially
S. Kopp (B) · R. Aylett · J. Gratch · P. L. Olivier · C. Pelachaud University of Bielefeld, Bielefeld, Germany e-mail:
[email protected]
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Auton Agent Multi-Agent Syst (2010) 20:1–2
imply a different emotional or cognitive internal state. A generation model is proposed based on results of an empirical study that explores the mapping between an observer’s attribution of emotional state to gaze. Morency et al. study how agents can better engage in natural face-to-face interactions by providing “backchannel feedback” to signal to the speaker that communication is working and that they should continue speaking. The authors investigate the use of sequential probabilistic models to automatically learn from a database of humanto-human interactions to predict listener backchannels from a speaker’s multimodal output features (e.g., prosody, spoken words and eye gaze). Austermann & Yamada tackle the related problem of understanding the user’s natural way of giving multimodal positive and negative feedback, but apply an interactive learning approach. In a human-robot teaching framework that uses different games, played collaboratively by the human user and an AIBO pet robot, the robot learns how to discriminate positive from negative feedback. We are grateful to the journal’s Editors-in-Chief, Jeffrey S. Rosenschein and M. Wooldridge, for supporting our initiative to publish this special issue. We are also very grateful to our Editorial Board: James Lester, Jean-Claude Martin, Zsofi Ruttkay, Christopher Peters, Sandy Louchart, Dirk Heylen, Britta Wrede, Eliabeth André, Marc Cavazza, Helmut Prendinger, Michael Kipp, Hannes Vilhjalmsson, Matthias Rehm, Stacy Marsella, Patrick Gebhard, and Ana Paiva. Most of all, we would like to thank the contributing authors for sharing their interesting and important research on intelligent virtual agents. We hope you enjoy this issue.
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