Publications

This page lists papers that cite, use, or mention NegMAS and its ecosystem (including SCML - Supply Chain Management League).

Note

This list is updated periodically using LLMs by searching academic databases. While we strive for accuracy, the automated process may occasionally miss papers or include incorrect information. Please double check these citations before reusing them. If you have published a paper using NegMAS that is not listed here, or if you notice any inaccuracies, please open an issue or submit a pull request.

Last updated: February 2026

How to Cite NegMAS

If you use NegMAS in your research, please cite the following paper:

@inproceedings{mohammad2021negmas,
  title={NegMAS: A Platform for Automated Negotiations},
  author={Mohammad, Yasser and Nakadai, Shinji and Greenwald, Amy},
  booktitle={PRIMA 2020: Principles and Practice of Multi-Agent Systems},
  pages={343--351},
  year={2021},
  publisher={Springer},
  doi={10.1007/978-3-030-69322-0_23}
}

Core NegMAS Papers

These are the main papers describing the NegMAS platform:

• Mohammad, Y., Nakadai, S., Greenwald, A. (2021). NegMAS: A Platform for Automated Negotiations. In: PRIMA 2020: Principles and Practice of Multi-Agent Systems. LNCS, vol 12568. Springer.

• Mohammad, Y., Nakadai, S., Greenwald, A. (2019). NegMAS: A Platform for Situated Negotiations. In: Twelfth International Workshop on Agent-based Complex Automated Negotiations (ACAN 2019).

• Mohammad, Y., Viqueira, E.A., Ayerza, N.A., Greenwald, A., Nakadai, S., Morinaga, S. (2019). Supply Chain Management World: A Benchmark Environment for Situated Negotiations. In: PRIMA 2019. LNCS, vol 11873. Springer. Cited by 38

Competition Papers (ANAC)

Papers describing the Automated Negotiating Agents Competition results using NegMAS/SCML:

• Aydoğan, R., Baarslag, T., Florijn, T.C.P., et al. (2025). The Automated Negotiating Agents Competition (ANAC) 2024 Challenges and Results. In: Proceedings of AAMAS 2025.

• Mohammad, Y., Nakadai, S., Greenwald, A. (2024). Automated Negotiation in Supply Chains: A Generalist Environment for RL/MARL Research. In: PRIMA 2024. LNCS. Springer.

• Aydoğan, R., Baarslag, T., Fujita, K., Hoos, H.H., et al. (2022). The 13th International Automated Negotiating Agent Competition Challenges and Results. In: IJCAI 2022 International Workshops. LNCS, vol 13752. Springer. Cited by 8

• Aydoğan, R., Baarslag, T., Fujita, K., Mell, J., et al. (2020). Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019. In: EUMAS 2020, AT 2020. LNCS, vol 12520. Springer. Cited by 51

Negotiation Strategies & Agents

Papers presenting novel negotiation strategies using NegMAS:

• Shymanski, J. (2025). ChargingBoul: A Competitive Negotiating Agent with Novel Opponent Modeling. arXiv:2512.06595.

• Chen, S., Weiss, G. (2025). Enhancing Agent-based Negotiation Strategies via Transfer Learning. Electronics. Cited by 2

• Miyajima, R., Fujita, K. (2025). CoCoNAT: Combinatorial Concurrent Negotiating Agent Transformer. SSRN Preprint.

• Florijn, T.C.P., Tijdeman, M., Yolum, P., Baarslag, T. (2025). Predicting the Outcome of Ongoing Automated Negotiations. In: PRIMA 2024. LNCS. Springer.

• 清水拓夢, 藤田桂英 (2024). サプライチェーンにおける合意可能価格予測を考慮した自動交渉戦略. 情報処理学会論文誌 (IPSJ Journal). Cited by 1

• Aguilera-Luzon, D., de Jonge, D., Larrosa, J. (2025). MiCRO for Multilateral Negotiations. In: PRIMA 2024. LNCS. Springer.

• Aguilera Luzón, D. (2025). New Variants of the MiCRO Negotiation Strategy. Master’s Thesis, Universitat Politècnica de Catalunya.

• Hassanvand, F., Nassiri-Mofakham, F., Fujita, K. (2024). Automated Negotiation Agents for Modeling Single-Peaked Bidders: An Experimental Comparison. Information. Cited by 1

• Chang, S., Fujita, K. (2024). COMB: Scalable Concession-driven Opponent Models Using Bayesian Learning. Group Decision and Negotiation. Cited by 3

• Miyajima, R., Fujita, K. (2024). Deep Reinforcement Learning Framework with Representation Learning for Concurrent Negotiation. In: ICAART 2024.

• Matsuo, H., Fujita, K. (2024). Effective Acceptance Strategy Using Deep Reinforcement Learning. Journal of Information Processing. Cited by 1

• Yoshino, H., Fujita, K. (2024). Clustering-Based Approach to Strategy Selection for Meta-Strategy in Automated Negotiation. In: ICAART 2024.

• Higa, R., Fujita, K., Takahashi, T., Shimizu, T., Morinaga, S. (2023). Reward-based Negotiating Agent Strategies. In: Proceedings of AAAI 2023. Cited by 16

• Chang, S., Fujita, K. (2023). A Scalable Opponent Model Using Bayesian Learning for Automated Bilateral Multi-issue Negotiation. In: Proceedings of AAMAS 2023. Cited by 5

• Chang, S., Fujita, K. (2023). Fine-Tuning Aggregation Convolutional Neural Network Surrogate Model. In: ICAART 2023. Cited by 1

• Hosokawa, Y., Fujita, K. (2023). Multi-Issue Negotiation Protocol with Pre-Domain Narrowing. Applied Sciences. Cited by 3

• Liu, Y., Hadfi, R., Ito, T. (2022). Concession Strategy Adjustment in Automated Negotiation Problems. In: IJCAI 2022 International Workshops. LNCS, vol 13752. Springer.

• Koça, T., Jonker, C.M., Baarslag, T. (2022). Enabling Negotiating Agents to Explore Very Large Outcome Spaces. In: IJCAI 2022 International Workshops. LNCS, vol 13752. Springer. Cited by 1

• Li, Z., Hadfi, R., Ito, T. (2022). Agenda-Based Automated Negotiation Through Utility Decomposition. In: IJCAI 2022 International Workshops. LNCS, vol 13752. Springer. Cited by 1

• Sengupta, A., Nakadai, S., Mohammad, Y. (2022). Transfer Learning Based Adaptive Automated Negotiating Agent Framework. In: Proceedings of IJCAI 2022. Cited by 6

• Ebrahimnezhad, A., Fujita, K. (2022). LuckyAgent2022: A Stop-Learning Multi-Armed Bandit Automated Negotiating Agent. In: ICCAE 2022. Cited by 1

• Sengupta, A., Mohammad, Y., Nakadai, S. (2021). An Autonomous Negotiating Agent Framework with Reinforcement Learning Based Strategies. arXiv:2102.03588. Cited by 48

• Mohammad, Y. (2021). Concurrent Local Negotiations with a Global Utility Function: A Greedy Approach. Autonomous Agents and Multi-Agent Systems, 35, 14. Cited by 14

• Yavuz, C.O.B., Süslü, Ç., Aydogan, R. (2020). Taking Inventory Changes into Account While Negotiating in Supply Chain Management. In: ICAART 2020. Cited by 4

Protocols & Theory

Papers on negotiation protocols and theoretical aspects:

• Mohammad, Y. (2025). Tackling the Protocol Problem in Automated Negotiation. In: Proceedings of AAMAS 2025. Cited by 1

• Florijn, T.C.P., Yolum, P., Baarslag, T. (2025). A Survey on One-to-Many Negotiation: A Taxonomy of Interdependency. In: Proceedings of IJCAI 2025. Cited by 1

• de Jonge, D. (2025). BINGO: An Algorithm for Automated Negotiations with Hidden Reservation Values. Technical Report.

• de Jonge, D. (2025). Introduction to Automated Negotiation. arXiv:2511.08659.

• Koça, T., de Jonge, D., Baarslag, T. (2024). Search Algorithms for Automated Negotiation in Large Domains. Annals of Mathematics and Artificial Intelligence. Cited by 3

• Mohammad, Y. (2023). Generalized Bargaining Protocols. In: AI 2023. LNCS, vol 14471. Springer. Cited by 3

• Mohammad, Y. (2023). Optimal Time-based Strategy for Automated Negotiation. Applied Intelligence, 53, 9088-9105. Cited by 9

• Mohammad, Y. (2023). Evaluating Automated Negotiations. In: IEEE WI-IAT 2023. Cited by 2

• Mohammad, Y. (2020). Optimal Deterministic Time-based Policy in Automated Negotiation. In: PRIMA 2020. LNCS, vol 12568. Springer. Cited by 4

• Li, Z., Hadfi, R., Ito, T. (2023). Divide-and-conquer in Automated Negotiations Through Utility Decomposition. IIAI Letters on Informatics and Interdisciplinary Research. Cited by 1

Preference Elicitation

Papers on preference elicitation during negotiation:

• Mohammad, Y., Nakadai, S. (2019). Optimal Value of Information Based Elicitation During Negotiation. In: Proceedings of AAMAS 2019. IFAAMAS. pp. 242-250.

• Mohammad, Y., Nakadai, S. (2018). FastVOI: Efficient Utility Elicitation During Negotiations. In: PRIMA 2018. LNCS, vol 11224. Springer. pp. 560-567.

Platforms & Frameworks

Papers describing other platforms that use or compare with NegMAS:

• Ebrahimnezhad, A., Fujita, K. (2023). NegoSim: A Modular and Extendable Automated Negotiation Simulation Platform Considering EUBOA. Applied Sciences. Cited by 7

• Doğru, A., Keskin, M.O., Aydoğan, R. (2025). Taking into Account Opponent’s Arguments in Human-Agent Negotiations. ACM Transactions on Interactive Intelligent Systems. Cited by 3

• Keskin, M.O., Buzcu, B., Koçyiğit, B., et al. (2024). NEGOTIATOR: A Comprehensive Framework for Human-Agent Negotiation. In: Proceedings of AAMAS 2024. Cited by 2

Applications

Papers applying NegMAS/SCML to real-world problems:

• Arakawa, R., Fujita, K. (2023). Deep Deterministic Policy Gradient for Nested Parallel Negotiation. In: IEEE WI-IAT 2023.

• Rincon, J.A., Costa, A., Julian, V., Carrascosa, C., et al. (2021). A Low-cost Human-Robot Negotiation System. In: PAAMS 2021. LNCS, vol 12946. Springer.

• Hirano, M., Matsushima, H., Izumi, K., Mukai, T. (2020). Simulation of Unintentional Collusion Caused by Auto Pricing in Supply Chain Markets. In: PRIMA 2020. LNCS, vol 12568. Springer. Cited by 3

• Inotsume, H., Aggarwal, A., Higa, R., Nakadai, S. (2020). Path Negotiation for Self-interested Multirobot Vehicles in Shared Space. In: IEEE/RSJ IROS 2020. Cited by 17

• Elakehal, E.E., Vennekens, J. (2021). A Logic-based Multiagent Product Configuration Model. In: IEEE ICICIP 2021.

Theses & Technical Reports

• Aguilera Luzón, D. (2025). New Variants of the MiCRO Negotiation Strategy. Master’s Thesis, Universitat Politècnica de Catalunya.

• Tijdeman, M. (2024). Predicting the Outcome of Automated Negotiations using Machine Learning. Master’s Thesis, Utrecht University.

• Cortés Sancho, F. (2021). Diseño de un Sistema de Negociación Bilateral entre Agentes. Bachelor’s Thesis, Universidad Politécnica de Madrid.

• Brown, I., Zhou, K., Sato, S., et al. (2023). g-RIPS Sendai 2023: SCML Agent Development. Technical Report, Tohoku University.

Books & Book Chapters

• Jonker, C.M., Siebert, L.C., et al. (2024). Reflective Hybrid Intelligence for Meaningful Human Control in Decision-Support Systems. In: Research Handbook on Responsible AI. Edward Elgar Publishing. Cited by 6

• Aydoğan, R., Ito, T., Moustafa, A., Zhang, M. (Eds.) (2021). Recent Advances in Agent-based Negotiation. Studies in Computational Intelligence, vol 958. Springer.

Survey Papers

Papers that survey the field and mention NegMAS:

• Dominguez, R., Cannella, S. (2020). Insights on Multi-agent Systems Applications for Supply Chain Management. Sustainability. Cited by 67

• Fujita, K. (2024). 私のブックマーク: 自動交渉 (My Bookmark: Automated Negotiation). Journal of the Japanese Society for Artificial Intelligence.