Towards Modeling Agent Negotiators by Analyzing Human Negotiation Behavior

Xu, Y., Sequeira, P. and Marsella, S. (2018) Towards Modeling Agent Negotiators by Analyzing Human Negotiation Behavior. In: Seventh International Conference on Affective Computing and Intelligent Interaction (ACII 2017), San Antonio, TX, USA, 23-26 Oct 2017, pp. 58-64. ISBN 9781538605639 (doi: 10.1109/ACII.2017.8273579)

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Negotiation is a fundamental aspect of social interaction. Our research aims to contribute towards the creation of artificial agent negotiators that can be used for training purposes to improve human negotiation skills. To achieve that, we address the challenge of identifying differences in human negotiation styles and relating those differences to individuals' personality traits. In particular, we follow a data-driven approach by collecting data on how people negotiate against an agent using a fixed-response strategy during a task involving the partition of a set of items. We then use different machine learning techniques to: 1) analyze the relationship between negotiation styles and personality traits; 2) characterize changes in the human negotiation behavior during the game; 3) discover human behavior patterns in response to different offers by the agent player. Our analyses show how different personality traits lead to distinct behaviors during the negotiation. In turn, this data will allow us to build agent negotiators that have a rich behavioral repertoire and are able to adapt to human negotiation trainees, thus fostering more interesting learning experiences.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Marsella, Professor Stacy
Authors: Xu, Y., Sequeira, P., and Marsella, S.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience

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