AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

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  • Johannes Gutenberg University Mainz
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Details

Original languageEnglish
Title of host publicationGECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion
Pages1-2
Number of pages2
ISBN (electronic)9798400704956
Publication statusPublished - 1 Aug 2024
Event2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion - Melbourne, Australia
Duration: 14 Jul 202418 Jul 2024

Abstract

This competition abstract provides a brief introduction to the AbstractSwarm Multi-Agent Logistics Competition, which runs in 2024 in the fourth year in series at the Genetic and Evolutionary Computation Conference (GECCO) and has been part of the IEEE World Congress on Computational Intelligence from 2021 to 2022. In this work, we also briefly introduce the AbstractSwarm multi-agent modeling and simulation system to provide a common starting point for researchers interested in the competition's rules and its challenges.

Keywords

    artificial intelligence, competition, logistics, multi-agent simulation, optimization

ASJC Scopus subject areas

Cite this

AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. / Apeldoorn, Daan; Dockhorn, Alexander; Panholzer, Torsten.
GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion. 2024. p. 1-2.

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Apeldoorn, D, Dockhorn, A & Panholzer, T 2024, AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. in GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion. pp. 1-2, 2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion, Melbourne, Australia, 14 Jul 2024. https://doi.org/10.1145/3638530.3664053
Apeldoorn, D., Dockhorn, A., & Panholzer, T. (2024). AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. In GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion (pp. 1-2) https://doi.org/10.1145/3638530.3664053
Apeldoorn D, Dockhorn A, Panholzer T. AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. In GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion. 2024. p. 1-2 doi: 10.1145/3638530.3664053
Apeldoorn, Daan ; Dockhorn, Alexander ; Panholzer, Torsten. / AbstractSwarm Multi-Agent Logistics Competition : Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion. 2024. pp. 1-2
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