A review of cooperation in multi-agent learning

Y Du, JZ Leibo, U Islam, R Willis, P Sunehag - arXiv preprint arXiv …, 2023 - arxiv.org
Cooperation in multi-agent learning (MAL) is a topic at the intersection of numerous
disciplines, including game theory, economics, social sciences, and evolutionary biology …

Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior

K Cui, S Hauck, C Fabian, H Koeppl - arXiv preprint arXiv:2307.06175, 2023 - arxiv.org
Recent reinforcement learning (RL) methods have achieved success in various domains.
However, multi-agent RL (MARL) remains a challenge in terms of decentralization, partial …

Adaptive incentive engineering in citizen-centric AI

B Koohy, J Buermann, S Stein, V Yazdanpanah… - 2024 - eprints.soton.ac.uk
Adaptive incentives are a valuable tool shown to improve the efficiency of complex
multiagent systems and could produce win-win situations for all stakeholders. However, their …

Partially Observable Multi-Agent Reinforcement Learning using Mean Field Control

K Cui, SH Hauck, C Fabian, H Koeppl - ICML 2024 Workshop: Aligning … - openreview.net
Recent reinforcement learning (RL) methods have achieved success in various domains.
However, multi-agent RL (MARL) remains a challenge in terms of decentralization, partial …

[PDF][PDF] Adaptive Incentive Engineering in Citizen-Centric AI

B Koohy, J Buermann, V Yazdanpanah, P Briggs… - ifaamas.csc.liv.ac.uk
Adaptive incentives are a valuable tool shown to improve the efficiency of complex
multiagent systems and could produce win-win situations for all stakeholders. However, their …

[HTML][HTML] Large-Scale Multi-Agent Reinforcement Learning via Mean Field Games

K Cui - tuprints.ulb.tu-darmstadt.de
In this dissertation, we discuss the mathematically rigorous multi-agent reinforcement
learning frameworks of mean field games (MFG) and mean field control (MFC). Dynamical …