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.
|Title of host publication||Proceedings of the 7th International Congress on Information and Communication Technology, ICICT'22|
|Publisher||Springer Nature Switzerland AG|
|Publication status||Accepted/In press - 21 Jan 2022|
|Name||Lecture Notes in Networks and Systems|