Visible to the public Towards Emotion-Aware Agents For Negotiation Dialogues

TitleTowards Emotion-Aware Agents For Negotiation Dialogues
Publication TypeConference Paper
Year of Publication2021
AuthorsChawla, Kushal, Clever, Rene, Ramirez, Jaysa, Lucas, Gale, Gratch, Jonathan
Conference Name2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)
Date Publishedsep
KeywordsAdaptation models, affective computing, Computational modeling, Computer architecture, conversational agents, decision making, Deep Learning, emotion models, Human Behavior, human-agent interaction, Metrics, negotiation dialogues, outcome prediction, Predictive models, pubcrawl, Scalability
AbstractNegotiation is a complex social interaction that encapsulates emotional encounters in human decision-making. Virtual agents that can negotiate with humans are useful in pedagogy and conversational AI. To advance the development of such agents, we explore the prediction of two important subjective goals in a negotiation - outcome satisfaction and partner perception. Specifically, we analyze the extent to which emotion attributes extracted from the negotiation help in the prediction, above and beyond the individual difference variables. We focus on a recent dataset in chat-based negotiations, grounded in a realistic camping scenario. We study three degrees of emotion dimensions - emoticons, lexical, and contextual by leveraging affective lexicons and a state-of-the-art deep learning architecture. Our insights will be helpful in designing adaptive negotiation agents that interact through realistic communication interfaces.
Citation Keychawla_towards_2021