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Adaptive Training for Aggression de-Escalation

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Artificial Life and Intelligent Agents (ALIA 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 519))

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Abstract

The ability to de-escalate confrontations with aggressive individuals is a useful skill, in particular within professions in public domains. Nevertheless, offering appropriate training that enables students to develop such skills is a nontrivial matter. As a complementary approach to real-world training, the STRESS project proposes a simulation-based environment for training of aggression de-escalation. The main focus of the current paper is to make this system adaptive to the performance of the trainee. To realize this, first a number of learning goals have been identified. Based on these, several levels of difficulty were established, as well as a mechanism to switch up and down between these levels based on the user’s score. A preliminary evaluation demonstrated that the system successfully adapts its difficulty level to the performance of the user, and that users are generally positive about the adaptation mechanism.

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Notes

  1. 1.

    Nevertheless, the project as a whole also explores other interaction modalities, such as speech, facial expressions and gestures.

  2. 2.

    Note that in some cases, answers that are unacceptable for one type of aggression may be exemplary for the other type. However, this is not necessarily always the case.

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Acknowledgments

This research was supported by funding from the National Initiative Brain and Cognition, coordinated by the Netherlands Organization for Scientific Research (NWO), under grant agreement No. 056-25-013.

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Correspondence to Tibor Bosse .

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Bosse, T., Gerritsen, C., de Man, J., Tolmeijer, S. (2015). Adaptive Training for Aggression de-Escalation. In: Headleand, C., Teahan, W., Ap Cenydd, L. (eds) Artificial Life and Intelligent Agents. ALIA 2014. Communications in Computer and Information Science, vol 519. Springer, Cham. https://doi.org/10.1007/978-3-319-18084-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-18084-7_7

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