Towards an Understanding of Default Policies in Multitask Policy Optimization

4 November 2021

Papers citing "Towards an Understanding of Default Policies in Multitask Policy Optimization"

9 / 9 papers shown

Title
Confronting Reward Model Overoptimization with Constrained RLHF Ted Moskovitz Aaditya K. Singh DJ Strouse T. Sandholm Ruslan Salakhutdinov Anca D. Dragan Stephen Marcus McAleer 34 47 0 06 Oct 2023
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs Theodore H. Moskovitz Brendan O'Donoghue Vivek Veeriah Sebastian Flennerhag Satinder Singh Tom Zahavy 42 19 0 02 Feb 2023
Understanding the Complexity Gains of Single-Task RL with a Curriculum Qiyang Li Yuexiang Zhai Yi Ma Sergey Levine 37 14 0 24 Dec 2022
Transfer RL via the Undo Maps Formalism Abhi Gupta Theodore H. Moskovitz David Alvarez-Melis Aldo Pacchiano OffRL 25 0 0 26 Nov 2022
Minimum Description Length Control Theodore H. Moskovitz Ta-Chu Kao M. Sahani M. Botvinick 26 1 0 17 Jul 2022
Joint Representation Training in Sequential Tasks with Shared Structure Aldo Pacchiano Ofir Nachum Nilseh Tripuraneni Peter L. Bartlett 33 5 0 24 Jun 2022
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress Rishabh Agarwal Max Schwarzer Pablo Samuel Castro Aaron C. Courville Marc G. Bellemare OffRL OnRL 26 63 0 03 Jun 2022
A First-Occupancy Representation for Reinforcement Learning Theodore H. Moskovitz S. Wilson M. Sahani 31 15 0 28 Sep 2021
Iterative Amortized Policy Optimization Joseph Marino Alexandre Piché Alessandro Davide Ialongo Yisong Yue OffRL 63 21 0 20 Oct 2020