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Reducing the Cost of Cycle-Time Tuning for Real-World Policy
  Optimization

Reducing the Cost of Cycle-Time Tuning for Real-World Policy Optimization

9 May 2023
Homayoon Farrahi
Rupam Mahmood
ArXivPDFHTML

Papers citing "Reducing the Cost of Cycle-Time Tuning for Real-World Policy Optimization"

5 / 5 papers shown
Title
Enabling Realtime Reinforcement Learning at Scale with Staggered
  Asynchronous Inference
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matthew D Riemer
G. Subbaraj
Glen Berseth
Irina Rish
OffRL
85
1
0
18 Dec 2024
Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning
Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning
Gautham Vasan
Yan Wang
Fahim Shahriar
James Bergstra
Martin Jägersand
A. R. Mahmood
27
2
0
29 Jun 2024
An Idiosyncrasy of Time-discretization in Reinforcement Learning
An Idiosyncrasy of Time-discretization in Reinforcement Learning
Kris De Asis
Richard S. Sutton
21
0
0
21 Jun 2024
Revisiting Scalable Hessian Diagonal Approximations for Applications in
  Reinforcement Learning
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed
Homayoon Farrahi
Felix Dangel
A. Rupam Mahmood
35
3
0
05 Jun 2024
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning
  Dexterous Manipulation Behaviors without Human Intervention
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta
Justin Yu
Tony Zhao
Vikash Kumar
Aaron Rovinsky
Kelvin Xu
Thomas Devlin
Sergey Levine
OffRL
72
95
0
22 Apr 2021
1