Poster · Atlanta

Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning

Name: Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning
Start: 2026-12-10T10:00:00-05:00
End: 2026-12-10T13:00:00-05:00
Location: Hall C1, Georgia World Congress Center

When: Thu 10 Dec 2026, 10:00–13:00 EST
Where: Hall C1, Georgia World Congress Center
Session: Atlanta Poster Session 3
Authors: Chulabhaya Wijesundara, Andrea Baisero, Zhongheng Li, Gregory D Castanon, Alan S Carlin, Christopher Amato
Organisations: Northeastern University, STR, University of California, Irvine, System Technology and Research, Boston University
QRS classification: Reinforcement learning

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