Work

The Regulatory Character of Boredom in AI - Towards a Self-Regulating System based on Spiking Neural Networks

Year: 2025

Type: conference-paper

Abstract: Boredom is increasingly recognized as a functional emotion playing an important role in regulating human behavior.Despite continuous advances in the field of artificial intelligence, research on whether these models can enter emotional states such as boredom remains limited.However, emotions can be pivotal towards more human-like intelligence in AI.This paper transfers the regulatory function of boredom into a control loop modeled with spiking neural networks.Simulations demonstrate the successful replication of the regulatory mechanism of boredom based on simulated input.This work provides a foundation for future research and development towards a self-regulating system based on spiking neural networks capable of entering a state of boredom.

Source: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)

DOI: 10.14428/esann/2025.es2025-5

Authors: Patrick Schoefer, James Danckert, Peter Stadler, Martin Bogdan

Institutions: University of Waterloo, Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University

Language: English

Topic: Psychiatry, Mental Health, Neuroscience

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze