Hugging Face Trending Papers
Jul 6

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas

Inducing cooperation among distributed agents is still a difficult problem in the field of multi-agent reinforcement learning (MARL), particularly in social dilemma situations. There, individual interests are misaligned with the common good and individual rationality leads to suboptimal group outcomes.

arXiv Machine Learning
Sep 4

Towards Scaling Reinforcement Learning to Massive Populations: Learning Mean-Field Representations

The paper proposes a mean‑field reinforcement learning framework that models rewards and transitions as functions of an unknown low‑dimensional aggregate statistic of a large agent population. By learning this low‑dimensional representation in an offline setting, the authors demonstrate a provable method for obtaining near‑optimal policies. Experiments on a one‑step routing game inspired by supply‑chain problems show that, with a fixed neural‑network size and optimization budget, the learned representation improves reward prediction and the quality of Nash equilibria compared to baselines that ignore population structure.

By Aditya Makkar, Benjamin Unger, Jeongyeol Kwon, Mathieu Lauri\`ere, Eugene Vinitsky, Yonathan Efroni
arXiv AI
Jul 7

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas

arXiv:2607. 04710v1 Announce Type: new Abstract: Inducing cooperation among distributed agents is still a difficult problem in the field of multi-agent reinforcement learning (MARL), particularly in social dilemma situations.

By Yu Wei, Yukiko Ogura, Yoshiyuki Ohmura, Ildefons Magrans de Abril, Hoshinori Kanazawa, Yasuo Kuniyoshi