Multi-Agent Behavior:
Properties,  computation and emergence
CVPR 2023

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
Nikunj Gupta (New York University); Samira Ebrahimi Kahou (École de Technologie Supérieure)

Bridging cognitive, statistical, and neural descriptions of multi-agent bird foraging behavior
Marjorie Xie (Basis Research Institute); Rafal Urbaniak (Basis Research Institute and Gdansk University); Emily Mackevicius (Basis Research Institute and Columbia University)

Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation
Wei-Jer Chang (University of California, Berkeley); Chen Tang (UC Berkeley); Chenran Li (University of California, Berkeley); Yeping Hu (University of California Berkeley); Masayoshi Tomizuka (MSC Lab); Wei Zhan (University of California, Berkeley)

Hierarchical Characterization of Social Behavior Motifs using Semi-Supervised Autoencoders
Daiyao Yi (University of Florida); Elizabeth S. Wright (University of Florida); Nancy Padilla-Coreano (University of Florida); Shreya Saxena (University of Florida)

StarCraftImage: A Large-Scale Dataset For Prototyping Spatial Reasoning Methods With Multi-Agent Behaviors

Sean Kulinski (Purdue University); Nicholas R Waytowich (US Army Research Laboratory); James Z Hare (DEVCOM Army Research Lab); David I Inouye (Purdue University)

Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images

Yunpeng Liu (University of British Columbia)*; Vasileios Lioutas (University of British Columbia); Jonathan w Lavington (University of British Columbia); Matthew Niedoba (University of British Columbia); Justice Sefas (University of British Columbia); Setareh Dabiri (Inverted AI); Dylan Green (Inverted AI); Xiaoxuan Liang (The University of British Columbia); Berend Zwartsenberg (Inverted AI); Adam Scibior (University of British Columbia); Frank Wood (University of British Columbia)