This book brings together the content that has been created over the past years in the context of AbstractSwarm. AbstractSwarm is a Multi-Agent Modeling and Simulation System for Logistics (and similar) scenarios. The main idea of the system is the strict separation of the scenario modeling ("what to do") and the agent behavior ("how to do it"). This results in a system where agents can in principle be put into arbitrary scenarios for improving the underlying processes. As a consequence, generic agent implementations are needed to cooperate in different kinds of scenarios. This small book is planned on the occasion of the 20th anniversary of AbstractSwarm for 2026 by the organization committee of the AbstractSwarm Multi-Agent Logistics Competition.
After providing some historical notes on the AbstractSwarm modeling and simulation system in Part I, Part II introduces technical aspects of the AbstractSwarm system. Part III concerns the AbstractSwarm Multi-Agent Competition, a competition held for four years (three of them with submissions) for finding the most adaptive agent implementations in the context of the AbstractSwarm system. Finally, Part IV gives an outlook on future work in the context of the AbstractSwarm system.
Table of Contents:
"Chapter-1.Historical Notes".- "Chapter-2.Once upon a time-A personal view at the beginnings of Abstract Swarm".- "Chapter-3.The Abstract Swarm System".- "Chapter-4.Graphical Modeling Language of the Abstract Swarm System".- "Chapter-5.Abstract Swarm Simulation System".- "ChaPTER-6.A Modular Interface for the Abstract Swarm Multi-Agent System".- "Chapter-7The Abstract Swarm Competition".- "Chapter-8.Abstract Swarm Multi-Agent Logistics Competition".- "Chapter-9.Evaluation Tool".- "Learning Agents".- "Chapter-10.Agents based on Self Organizing Maps".- "Chapter-11.Agents based on Program Trees and Genetic Algorithms".- "Chapter-12.Evaluation of the Scenarios".- "Chapter-13.Outlook and Future Work".- "Chapter-14.Outlook and Future Work of Abstract Swarm".
About the Author :
Daan Apeldoorn works for the Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI) at the University Medical Center of the Johannes Gutenberg University Mainz and is a professor of computer science in the dual study program at IU International University of Applied Sciences, Germany. He received his bachelor's degree from Johannes Gutenberg University Mainz, his master's degree from FernUniversität in Hagen and his doctoral degree from TU Dortmund University. His research interests focus on agent-based simulations and knowledge representation in the context of learning agents and decision support systems.
Alexander Dockhorn is an Associate Professor at the Metaverse Lab of the University of Southern Denmark (SDU) in Odense, where he works on artificial intelligence in games and its transfer to broader applications. He earned his B.Sc., M.Sc., and PhD in Computer Science from Otto von Guericke University Magdeburg (OVGU). His postdoctoral work spans Queen Mary University of London and OVGU, followed by a Junior Professorship at Leibniz University Hannover. His current research focuses on the identification and exploitation of abstractions in decision-making agents and decision-support systems for hybrid intelligence.
Torsten Panholzer is Head of the Division of Medical Informatics at the Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), a department of the University Medical Center at Johannes Gutenberg University Mainz. He holds a PhD in natural sciences from the Johannes Gutenberg University Mainz. Subsequently, he worked as a Data Processing Analyst and Software Engineer at two Tech firms before joining IMBEI as a Research Associate. His current work focuses on system and data integration, identity management, and artificial intelligence.
