Simplifying Model-based RL: Learning Representations, Latent-space
Models, and Policies with One Objective

Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective

18 September 2022

Homanga Bharadhwaj

Benjamin Eysenbach

Ruslan Salakhutdinov

Papers citing "Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective"

7 / 7 papers shown

Title
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 33 1 0 11 Oct 2024
UniZero: Generalized and Efficient Planning with Scalable Latent World Models Yuan Pu Yazhe Niu Jiyuan Ren Zhenjie Yang Hongsheng Li Yu Liu OffRL 28 1 0 15 Jun 2024
DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning Weikang Wan Ziyu Wang Zackory M. Erickson David Held David Held 19 4 0 08 Feb 2024
Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni Benjamin Eysenbach Erfan Seyedsalehi Michel Ma Clement Gehring Aditya Mahajan Pierre-Luc Bacon AI4TS AI4CE 8 20 0 17 Jan 2024
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach Alexander Khazatsky Sergey Levine Ruslan Salakhutdinov OffRL 174 32 0 06 Oct 2021
Model-based Policy Optimization with Unsupervised Model Adaptation Jian Shen Han Zhao Weinan Zhang Yong Yu 22 25 0 19 Oct 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 321 1,662 0 04 May 2020