A Second-Order Adaptive Network Model for Collective Emotional Response during Reward-Based Gaming

Harry Thavaganeshan, Joy Wu, Jan Treur

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

Abstract

In this paper, a second-order adaptive self-modeling network model is introduced to model collective emotional response during frequent repetitive reward-based gaming. The model makes use of organizational learning using sharing individual learning over shared gaming experiences. Simulation showed a relevant prediction of skill-building affected by emotional responses and context factors concerning communication and listening. The dynamics of the model were verified and validated through mathematical verification and parameter tuning, resulting in a computational model with a potential of being a successful cornerstone for frequent repetitive reward-based gaming-related research.
Original languageEnglish
Title of host publicationProceedings of the 7th International Congress on Information and Communication Technology, ICICT'22
PublisherSpringer Nature Switzerland AG
Publication statusAccepted/In press - 21 Jan 2022

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer Nature

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