ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2201.02874
  4. Cited By
Assessing Policy, Loss and Planning Combinations in Reinforcement
  Learning using a New Modular Architecture

Assessing Policy, Loss and Planning Combinations in Reinforcement Learning using a New Modular Architecture

8 January 2022
Tiago Gaspar Oliveira
Arlindo L. Oliveira
ArXivPDFHTML

Papers citing "Assessing Policy, Loss and Planning Combinations in Reinforcement Learning using a New Modular Architecture"

6 / 6 papers shown
Title
Visualizing MuZero Models
Visualizing MuZero Models
Joery A. de Vries
K. Voskuil
Thomas M. Moerland
Aske Plaat
62
9
0
25 Feb 2021
Combining Off and On-Policy Training in Model-Based Reinforcement
  Learning
Combining Off and On-Policy Training in Model-Based Reinforcement Learning
Alexandre Borges
Arlindo L. Oliveira
87
2
0
24 Feb 2021
Learning to Play Two-Player Perfect-Information Games without Knowledge
Learning to Play Two-Player Perfect-Information Games without Knowledge
Quentin Cohen-Solal
OffRL
70
13
0
03 Aug 2020
Combining Q-Learning and Search with Amortized Value Estimates
Combining Q-Learning and Search with Amortized Value Estimates
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
Tobias Pfaff
T. Weber
Lars Buesing
Peter W. Battaglia
OffRL
67
48
0
05 Dec 2019
Thinking Fast and Slow with Deep Learning and Tree Search
Thinking Fast and Slow with Deep Learning and Tree Search
Thomas W. Anthony
Zheng Tian
David Barber
100
396
0
23 May 2017
OpenAI Gym
OpenAI Gym
Greg Brockman
Vicki Cheung
Ludwig Pettersson
Jonas Schneider
John Schulman
Jie Tang
Wojciech Zaremba
OffRL
ODL
223
5,077
0
05 Jun 2016
1