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2025

Bibliographic References tagged with 2025

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D. Goktas et al.,
D. Goktas et al.,
A. Shah et al.,
Learning from synthetic labs: Language models as auction participants”, arXiv preprint arXiv:2507.09083 , 2025.
A. Shah et al.,
Learning from synthetic labs: Language models as auction participants”, arXiv preprint arXiv:2507.09083 , 2025.
Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
Pricing with tips in three-sided delivery platforms”, arXiv preprint arXiv:2507.10872, 2025.
Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
Pricing with tips in three-sided delivery platforms”, arXiv preprint arXiv:2507.10872, 2025.
E. Soumalias, Y. Jiang, K. Zhu, M. Curry, S. Seuken, and D. C. Parkes,
E. Soumalias, Y. Jiang, K. Zhu, M. Curry, S. Seuken, and D. C. Parkes,
T. Wang, H. Dong, Y. Jiang, D. C. Parkes, and M. Tambe,
On diffusion models for multi-agent partial observability: Shared attractors, error bounds, and composite flow”, Proc. 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025. pp. 2143–2152, 2025.
T. Wang, H. Dong, Y. Jiang, D. C. Parkes, and M. Tambe,
On diffusion models for multi-agent partial observability: Shared attractors, error bounds, and composite flow”, Proc. 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025. pp. 2143–2152, 2025.
A. Tacchetti et al.,
Deep mechanism design: Learning social and economic policies for human benefit.”, Proceedings of the National Academy of Sciences of the United States of America, vol. 122, no. 25, p. e2319949121, 2025, doi: 10.1073/pnas.2319949121.
A. Tacchetti et al.,
Deep mechanism design: Learning social and economic policies for human benefit.”, Proceedings of the National Academy of Sciences of the United States of America, vol. 122, no. 25, p. e2319949121, 2025, doi: 10.1073/pnas.2319949121.