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2020 – today
- 2024
[j1]Farzane Aminmansour, Taher Jafferjee, Ehsan Imani, Erin J. Talvitie, Michael Bowling, Martha White:
Mitigating Value Hallucination in Dyna-Style Planning via Multistep Predecessor Models. J. Artif. Intell. Res. 80: 441-473 (2024)- 2023
- [c5]David Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Wenbin Song, Feifei Tong, Matthew E. Taylor, Tianpei Yang, Zipeng Dai, Hui Chen, Jiangcheng Zhu, Kun Shao, Jun Wang, Yaodong Yang:
Learning to Shape Rewards Using a Game of Two Partners. AAAI 2023: 11604-11612 - [c4]David Henry Mguni, Haojun Chen, Taher Jafferjee, Jianhong Wang, Longfei Yue, Xidong Feng, Stephen Marcus McAleer, Feifei Tong, Jun Wang, Yaodong Yang:
MANSA: Learning Fast and Slow in Multi-Agent Systems. ICML 2023: 24631-24658 - [i8]David Mguni, Taher Jafferjee, Haojun Chen, Jianhong Wang, Long Fei, Xidong Feng, Stephen McAleer, Feifei Tong, Jun Wang, Yaodong Yang:
MANSA: Learning Fast and Slow in Multi-Agent Systems. CoRR abs/2302.05910 (2023) - 2022
- [c3]David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang:
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. ICLR 2022 - [c2]Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou-Ammar:
Reinforcement Learning in Presence of Discrete Markovian Context Evolution. ICLR 2022 - [c1]Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Henry Mguni, Jun Wang, Haitham Ammar:
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. ICML 2022: 20423-20443 - [i7]Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou-Ammar:
Reinforcement Learning in Presence of Discrete Markovian Context Evolution. CoRR abs/2202.06557 (2022) - [i6]Aivar Sootla, Alexander I. Cowen-Rivers, Taher Jafferjee, Ziyan Wang, David Mguni, Jun Wang, Haitham Bou-Ammar:
SAUTE RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. CoRR abs/2202.06558 (2022) - [i5]Taher Jafferjee, Juliusz Krysztof Ziomek, Tianpei Yang, Zipeng Dai, Jianhong Wang, Matthew E. Taylor, Kun Shao, Jun Wang, David Mguni:
Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training. CoRR abs/2209.01054 (2022) - 2021
- [i4]David Mguni, Jianhong Wang, Taher Jafferjee, Nicolas Perez Nieves, Wenbin Song, Yaodong Yang, Feifei Tong, Hui Chen, Jiangcheng Zhu, Yali Du, Jun Wang:
Learning to Shape Rewards using a Game of Switching Controls. CoRR abs/2103.09159 (2021) - [i3]David Mguni, Joel Jennings, Taher Jafferjee, Aivar Sootla, Yaodong Yang, Changmin Yu, Usman Islam, Ziyan Wang, Jun Wang:
DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention. CoRR abs/2110.14468 (2021) - [i2]David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang:
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. CoRR abs/2112.02618 (2021) - 2020
- [i1]Taher Jafferjee, Ehsan Imani, Erin Talvitie, Martha White, Michael Bowling:
Hallucinating Value: A Pitfall of Dyna-style Planning with Imperfect Environment Models. CoRR abs/2006.04363 (2020)
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