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Sharing Knowledge in Multi-Task Deep Reinforcement Learning

Sharing Knowledge in Multi-Task Deep Reinforcement Learning

17 January 2024
Carlo DÉramo
Davide Tateo
Andrea Bonarini
Marcello Restelli
Jan Peters
ArXivPDFHTML

Papers citing "Sharing Knowledge in Multi-Task Deep Reinforcement Learning"

20 / 20 papers shown
Title
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
Siyuan Mu
Sen Lin
MoE
126
1
0
10 Mar 2025
One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
Nico Bohlinger
Grzegorz Czechmanowski
Maciej Krupka
Piotr Kicki
Krzysztof Walas
Jan Peters
Davide Tateo
42
12
0
10 Sep 2024
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
Ying Fan
Jingling Li
Adith Swaminathan
Aditya Modi
Ching-An Cheng
OffRL
70
0
0
14 Aug 2024
The Power of Active Multi-Task Learning in Reinforcement Learning from Human Feedback
The Power of Active Multi-Task Learning in Reinforcement Learning from Human Feedback
Ruitao Chen
Liwei Wang
67
1
0
18 May 2024
Active Exploration in Bayesian Model-based Reinforcement Learning for
  Robot Manipulation
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation
Carlos Plou
Ana C. Murillo
Ruben Martinez-Cantin
OffRL
32
0
0
02 Apr 2024
Provable Benefits of Multi-task RL under Non-Markovian Decision Making
  Processes
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang
Yuan-Chia Cheng
Jing Yang
Vincent Tan
Yingbin Liang
26
0
0
20 Oct 2023
Robust Knowledge Transfer in Tiered Reinforcement Learning
Robust Knowledge Transfer in Tiered Reinforcement Learning
Jiawei Huang
Niao He
OffRL
21
1
0
10 Feb 2023
Multi-Environment Pretraining Enables Transfer to Action Limited
  Datasets
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets
David Venuto
Sherry Yang
Pieter Abbeel
Doina Precup
Igor Mordatch
Ofir Nachum
OffRL
20
5
0
23 Nov 2022
Provable Benefits of Representational Transfer in Reinforcement Learning
Provable Benefits of Representational Transfer in Reinforcement Learning
Alekh Agarwal
Yuda Song
Wen Sun
Kaiwen Wang
Mengdi Wang
Xuezhou Zhang
OffRL
21
33
0
29 May 2022
Nearly Minimax Algorithms for Linear Bandits with Shared Representation
Nearly Minimax Algorithms for Linear Bandits with Shared Representation
Jiaqi Yang
Qi Lei
Jason D. Lee
S. Du
35
16
0
29 Mar 2022
PAC-Bayesian Lifelong Learning For Multi-Armed Bandits
PAC-Bayesian Lifelong Learning For Multi-Armed Bandits
H. Flynn
David Reeb
M. Kandemir
Jan Peters
22
7
0
07 Mar 2022
Non-Stationary Representation Learning in Sequential Linear Bandits
Non-Stationary Representation Learning in Sequential Linear Bandits
Yuzhen Qin
Tommaso Menara
Samet Oymak
ShiNung Ching
Fabio Pasqualetti
OffRL
29
17
0
13 Jan 2022
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication
  Pattern Recognition Module
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module
Wei-Cheng Tseng
Wei Wei
Da-Cheng Juan
Min Sun
31
2
0
14 Dec 2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Tianhe Yu
Aviral Kumar
Yevgen Chebotar
Karol Hausman
Sergey Levine
Chelsea Finn
OffRL
24
78
0
16 Sep 2021
Evolving Hierarchical Memory-Prediction Machines in Multi-Task
  Reinforcement Learning
Evolving Hierarchical Memory-Prediction Machines in Multi-Task Reinforcement Learning
Stephen Kelly
Tatiana Voegerl
W. Banzhaf
C. Gondro
43
13
0
23 Jun 2021
On the Power of Multitask Representation Learning in Linear MDP
On the Power of Multitask Representation Learning in Linear MDP
Rui Lu
Gao Huang
S. Du
19
28
0
15 Jun 2021
Randomized Value Functions via Posterior State-Abstraction Sampling
Randomized Value Functions via Posterior State-Abstraction Sampling
Dilip Arumugam
Benjamin Van Roy
OffRL
28
7
0
05 Oct 2020
Multi-Task Learning with Deep Neural Networks: A Survey
Multi-Task Learning with Deep Neural Networks: A Survey
M. Crawshaw
CVBM
25
608
0
10 Sep 2020
Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Amy Zhang
Shagun Sodhani
Khimya Khetarpal
Joelle Pineau
27
5
0
14 Jul 2020
Deep Reinforcement and InfoMax Learning
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure
Rémi Tachet des Combes
T. Doan
Philip Bachman
R. Devon Hjelm
AI4CE
17
108
0
12 Jun 2020
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