Zavlanos, Michael M.

10 publications

ICML 2025 Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping Guangyi Liu, Suzan Iloglu, Michael Caldara, Joseph W Durham, Michael M. Zavlanos

ICML 2025 Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen, Giorgos Stamou, Michael M. Zavlanos, George Vouros

TMLR 2025 LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning Pingcheng Jian, Xiao Wei, Yanbaihui Liu, Samuel A. Moore, Michael M. Zavlanos, Boyuan Chen

NeurIPS 2024 Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport Zifan Wang, Yi Shen, Michael M. Zavlanos, Karl H. Johansson

TMLR 2024 Perception Stitching: Zero-Shot Perception Encoder Transfer for Visuomotor Robot Policies Pingcheng Jian, Easop Lee, Zachary I. Bell, Michael M. Zavlanos, Boyuan Chen

L4DC 2023 Physics-Guided Active Learning of Environmental Flow Fields Reza Khodayi-mehr, Pingcheng Jian, Michael M. Zavlanos

L4DC 2023 Policy Evaluation in Distributional LQR Zifan Wang, Yulong Gao, Siyi Wang, Michael M. Zavlanos, Alessandro Abate, Karl Henrik Johansson

CoRL 2023 Policy Stitching: Learning Transferable Robot Policies Pingcheng Jian, Easop Lee, Zachary Bell, Michael M. Zavlanos, Boyuan Chen

LoG 2023 Transferable Hypergraph Neural Networks via Spectral Similarity Mikhail Hayhoe, Hans Matthew Riess, Michael M. Zavlanos, Victor Preciado, Alejandro Ribeiro

L4DC 2021 Learning Without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning Chenyu Liu, Yan Zhang, Yi Shen, Michael M. Zavlanos