Jakub Grudzien Kuba

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 17

Top Topics

Partially Observable Markov Decision Processes

Reinforcement Learning

Top Venues

Publications

Jakub Grudzien Kuba, Masatoshi Uehara, Pieter Abbeel, Sergey Levine
Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. CoRR (2024)
Shangding Gu, Jakub Grudzien Kuba, Yuanpei Chen, Yali Du, Long Yang, Alois C. Knoll, Yaodong Yang
Safe multi-agent reinforcement learning for multi-robot control. Artif. Intell. 319 (2023)
Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine
IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies. CoRR (2023)
Yifan Zhong, Jakub Grudzien Kuba, Siyi Hu, Jiaming Ji, Yaodong Yang
Heterogeneous-Agent Reinforcement Learning. CoRR (2023)
Jakub Grudzien Kuba, Christian Schröder de Witt, Jakob N. Foerster
Mirror Learning: A Unifying Framework of Policy Optimisation. CoRR (2022)
Muning Wen, Jakub Grudzien Kuba, Runji Lin, Weinan Zhang, Ying Wen, Jun Wang, Yaodong Yang
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem. CoRR (2022)
Zehao Dou, Jakub Grudzien Kuba, Yaodong Yang
Understanding Value Decomposition Algorithms in Deep Cooperative Multi-Agent Reinforcement Learning. CoRR (2022)
Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster
Discovered Policy Optimisation. CoRR (2022)
Muning Wen, Jakub Grudzien Kuba, Runji Lin, Weinan Zhang, Ying Wen, Jun Wang, Yaodong Yang
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem. NeurIPS (2022)
Jakub Grudzien Kuba, Xidong Feng, Shiyao Ding, Hao Dong, Jun Wang, Yaodong Yang
Heterogeneous-Agent Mirror Learning: A Continuum of Solutions to Cooperative MARL. CoRR (2022)
Jakub Grudzien Kuba, Christian A. Schröder de Witt, Jakob N. Foerster
Mirror Learning: A Unifying Framework of Policy Optimisation. ICML (2022)
Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun, Jun Wang, Yaodong Yang
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning. ICLR (2022)
Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster
Discovered Policy Optimisation. NeurIPS (2022)
Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun, Jun Wang, Yaodong Yang
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning. CoRR (2021)
Jakub Grudzien Kuba, Muning Wen, Yaodong Yang, Linghui Meng, Shangding Gu, Haifeng Zhang, David Henry Mguni, Jun Wang
Settling the Variance of Multi-Agent Policy Gradients. CoRR (2021)
Shangding Gu, Jakub Grudzien Kuba, Muning Wen, Ruiqing Chen, Ziyan Wang, Zheng Tian, Jun Wang, Alois C. Knoll, Yaodong Yang
Multi-Agent Constrained Policy Optimisation. CoRR (2021)
Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Shangding Gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang
Settling the Variance of Multi-Agent Policy Gradients. NeurIPS (2021)