Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/60094
Title: Integrating Personality and Mood with Agent Emotions
Contributor(s): Ojha, Suman (author); Vitale, Jonathan  (author)orcid ; Raza, Syed Ali (author); Billingsley, Richard (author); Williams, Mary-Anne (author)
Publication Date: 2019
Handle Link: https://hdl.handle.net/1959.11/60094
Abstract: 

An intelligent agent should be able to show different emotional behaviours in different interaction situations to become believable and establish close relationships with human counterparts. It is widely accepted that personality and mood play an important role in modulating emotions. However, current computational accounts of emotion for intelligent agents do not effectively integrate the notions of personality and mood in the process of emotion generation. Previous attempts that have been made are mostly based on the assumptions of the researcher, rather than on empirical data and scientific validation. In this paper, we present the results of a novel supervised machine learning approach used to train a network of emotions that integrates the factors of personality and mood, which provides a high emotion intensity prediction accuracy.

Publication Type: Conference Publication
Conference Details: International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, 13th to 17th of May, 2019
Source of Publication: Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), v.18, p. 2147-2149
Fields of Research (FoR) 2020: 4601 Applied computing
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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