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Engineering the Next Generation of Multi-agent Systems: A Community Roadmap from EMAS 2025

Title: Engineering the Next Generation of Multi-agent Systems: A Community Roadmap from EMAS 2025
Authors: Rodriguez, Sebastian; Bairy, Akhila; Baldoni, Matteo; Benjamin, Patrick; Blessing, Constantin; Brandstetter, Nicolas; Chopra, Amit K.; Clemen, Thomas; Dennis, Louise A.; Esmaeili, Ahmad; Feng, Lu; Ferrando, Angelo; Ghorrati, Zahra; Guillet, Victor; Gürcan, Önder; Hans, Soham; Herber, James; Mascardi, Viviana; Mauri, Marcel; Müller, Jörg P.; Thangarajah, John; Tyl, Rafał; Yang, Yi
Source: Rodriguez, S, Bairy, A, Baldoni, M, Benjamin, P, Blessing, C, Brandstetter, N, Chopra, A K, Clemen, T, Dennis, L A, Esmaeili, A, Feng, L, Ferrando, A, Ghorrati, Z, Guillet, V, Gürcan, Ö, Hans, S, Herber, J, Mascardi, V, Mauri, M, Müller, J P, Thangarajah, J, Tyl, R & Yang, Y 2026, Engineering the Next Generation of Multi-agent Systems: A Community Roadmap from EMAS 2025. in Engineering Multi-Agent Systems (EMAS 2025) . vol. 16407, Chapter 14, Engineering Multi-Agent Systems, vol. 16407, Springer Cham, pp. 238-258. https://doi.org/10.1007/978-3-032-18011-7_14
Publisher Information: Springer Cham
Publication Year: 2026
Collection: The University of Manchester: Research Explorer - Publications
Description: This paper presents the outcomes of an open-floor session held at the 13th International Workshop on Engineering Multi-Agent Systems (EMAS 2025), aimed at co-developing a research roadmap for the EMAS community. Participants collaboratively identified and prioritised challenges in engineering large-scale, adaptive multiagent systems, particularly considering the need to engineer systems that can seamlessly integrate learning and reasoning. Through structured group discussions, four key challenges emerged: explainability in heterogeneous environments, environment modeling, handling dynamic contexts, and communication standardisation. For each of the challenges, participants proposed and ranked potential solutions based on impact and effort. The resulting roadmap highlights concrete research directions toward engineering intelligent, explainable, and interoperable multiagent systems that effectively integrate reasoning and learning in dynamic environments.
Document Type: conference object
File Description: application/pdf
Language: English
Relation: info:eu-repo/semantics/altIdentifier/isbn/978-3-032-18010-0
DOI: 10.1007/978-3-032-18011-7_14
Availability: https://research.manchester.ac.uk/en/publications/e127c282-c2b7-4b90-a5d0-4c61a072d091; https://doi.org/10.1007/978-3-032-18011-7_14; https://pure.manchester.ac.uk/ws/files/1825510647/EMAS2025_Roadmap.pdf; https://link.springer.com/10.1007/978-3-032-18011-7_14
Rights: info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.5C7B722F
Database: BASE