Jakub Grudzien Kuba

According to our database, Jakub Grudzien Kuba authored at least 16 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Offline Materials Optimization with CliqueFlowmer.

Jakub Grudzien Kuba, Benjamin Kurt Miller, Sergey Levine, Pieter Abbeel

CoRR, March, 2026

Cliqueformer: Model-Based Optimization with Structured Transformers.

Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Language Self-Play For Data-Free Training.

Jakub Grudzien Kuba, Mengting Gu, Qi Ma, Yuandong Tian, Vijai Mohan

CoRR, September, 2025

2024

Heterogeneous-Agent Reinforcement Learning.

Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng, Siyi Hu, Jiaming Ji, Yaodong Yang

J. Mach. Learn. Res., 2024

Functional Graphical Models: Structure Enables Offline Data-Driven Optimization.

Jakub Grudzien Kuba, Masatoshi Uehara, Pieter Abbeel, Sergey Levine

CoRR, 2024

2023

Safe multi-agent reinforcement learning for multi-robot control.

Shangding Gu, Jakub Grudzien Kuba, Yuanpei Chen, Yali Du, Long Yang, Alois C. Knoll, Yaodong Yang

Artif. Intell., June, 2023

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine

CoRR, 2023

Heterogeneous-Agent Reinforcement Learning.

Yifan Zhong, Jakub Grudzien Kuba, Siyi Hu, Jiaming Ji, Yaodong Yang

CoRR, 2023

2022

Heterogeneous-Agent Mirror Learning: A Continuum of Solutions to Cooperative MARL.

Jakub Grudzien Kuba, Xidong Feng, Shiyao Ding, Hao Dong, Jun Wang, Yaodong Yang

CoRR, 2022

Understanding Value Decomposition Algorithms in Deep Cooperative Multi-Agent Reinforcement Learning.

Zehao Dou, Jakub Grudzien Kuba, Yaodong Yang

CoRR, 2022

Multi-Agent Reinforcement Learning is a Sequence Modeling Problem.

Muning Wen, Jakub Grudzien Kuba, Runji Lin, Weinan Zhang, Ying Wen, Jun Wang, Yaodong Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discovered Policy Optimisation.

Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Mirror Learning: A Unifying Framework of Policy Optimisation.

Jakub Grudzien Kuba, Christian A. Schröder de Witt, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning.

Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun, Jun Wang, Yaodong Yang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Multi-Agent Constrained Policy Optimisation.

Shangding Gu, Jakub Grudzien Kuba, Muning Wen, Ruiqing Chen, Ziyan Wang, Zheng Tian, Jun Wang, Alois C. Knoll, Yaodong Yang

CoRR, 2021

Settling the Variance of Multi-Agent Policy Gradients.

Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Shangding Gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021