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Predicting User Psychological Characteristics from Interactions with Empathetic Virtual Agents
Enabling virtual agents to quickly and accurately infer users' psychological characteristics such as their personality could support a broad range of applications in education, training, and entertainment. With a focus on narrative-centered learning environments, this paper presents an inductive framework for inferring users' psychological characteristics from observations of their interactions with virtual agents. Trained on traces of users' interactions with virtual agents in the environment, psychological user models are induced from the interactions to accurately infer different aspects of a user's personality. Further, analyses of timing data suggest that these induced models are also able to converge on correct predictions after a relatively small number of interactions with virtual agents.
| Download Paper | |
| Full Title | Predicting User Psychological Characteristics from Interactions with Empathetic Virtual Agents |
| Year | 2009 |
| Language | English |
| Book | Intelligent Virtual Agents - IVA 2009 |
| Keywords | User modeling, adaptive agents, Evaluation, virtual agents, Affective interaction, empathy |
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