Emotion-controlled communication in agent networks

Communication within agent networks involves multiple input and output parameters, making adaptive control and interpretation difficult. Existing systems typically rely on fixed rules or reactive behavior, lacking mechanisms for self-regulation or proactive engagement. This paper proposes an emotion-controlled communication framework, where internal emotional states act as an intermediate layer between input stimuli and output generation. Emotions are modeled using analog circuits to simulate continuous accumulation, decay, and inter-emotional feedback. Simulations with two agents — one active, one passive — demonstrate how internal states evolve in response to input and influence communication behavior over time.

Metadaten
Author:	Yanakorn Ruamsuk, Herwig Unger
URN:	urn:nbn:de:bvb:384-opus4-1252597
Frontdoor URL	https://opus.bibliothek.uni-augsburg.de/opus4/125259
Parent Title (English):	3rd Workshop on Machine Learning in Networking (MaLeNe), co-located with the 6th International Conference on Networked Systems (NetSys 2025), Ilmenau, Germany, September 1, 2025: proceedings
Publisher:	Universität Augsburg
Place of publication:	Augsburg
Editor:	Michael SeufertORCiD GND, Andreas Blenk, Björn Richerzhagen
Type:	Conference Proceeding
Language:	English
Date of Publication (online):	2025/09/15
Year of first Publication:	2025
Publishing Institution:	Universität Augsburg
Release Date:	2025/09/16
Institutes:	Fakultät für Angewandte Informatik
	Fakultät für Angewandte Informatik / Institut für Informatik
	Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Vernetzte Systeme und Kommunikationsnetze
Dewey Decimal Classification:	0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):	CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)

Open Access