Agent Societies
Online Relational Inference for Evolving Multi-agent Interacting Systems
Table 1: Comparison of key features between prior works and this work. Method Description Model Consider Evolution in Criteria Agnostic Interaction Parameter Dynamics Acc.
Multi-Agent Common Knowledge Reinforcement Learning
Christian Schroeder de Witt, Jakob Foerster, Gregory Farquhar, Philip Torr, Wendelin Boehmer, Shimon Whiteson
Neural Information Processing Systems http://nips.cc/
Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning Jianzhun Shao, Y un Qu
MARL in real scenarios is still challenging due to the same safety and efficiency concerns in single-agent setting, then it is worth conducting investigation for offline RL in multi-agent setting.
A Diffusion-Model of Joint Interactive Navigation Matthew Niedoba 1,2 J. Wilder Lavington
Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors.
Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
Multi-Agent Reinforcement Learning (GoMARL), which learns automatic grouping without domain knowledge for efficient cooperation.