Learning to Explain Anger: An Adaptive Humanoid-Agent for Cyber-Aggression

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

28 Downloads (Pure)

Abstract

Social media is one of the widely used channels for interpersonal communication, and to give personal feedback. However, negative feedback can affect esteem and mental health of a person. This paper presents a computational network model of a humanoid agent for getting inappropriate feedback, who learns to react with a level of competence on aggression due to feedback. This model can serve as an input to detect and handle cyber-aggression.
Original languageEnglish
Title of host publicationPRIMA 2019: Principles and Practice of Multi-Agent Systems
Subtitle of host publication22nd International Conference, Turin, Italy, October 28–31, 2019, Proceedings
EditorsMatteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
PublisherSpringer
Pages559-567
Number of pages9
ISBN (Electronic)9783030337926
ISBN (Print)9783030337919
DOIs
Publication statusPublished - 2019
Event22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, Italy
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11873 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
Country/TerritoryItaly
CityTurin
Period28/10/1931/10/19

Keywords

  • Agent based modelling
  • Computational model
  • Cyber-aggression

Fingerprint

Dive into the research topics of 'Learning to Explain Anger: An Adaptive Humanoid-Agent for Cyber-Aggression'. Together they form a unique fingerprint.

Cite this