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. 1902.00843
  4. Cited By
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

3 February 2019
Francisco M. Garcia
Philip S. Thomas
ArXivPDFHTML

Papers citing "A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning"

14 / 14 papers shown
Title
Reinforcement Teaching
Reinforcement Teaching
Alex Lewandowski
Calarina Muslimani
Dale Schuurmans
Matthew E. Taylor
Jun Luo
81
1
0
28 Jan 2025
A Survey of Meta-Reinforcement Learning
A Survey of Meta-Reinforcement Learning
Jacob Beck
Risto Vuorio
E. Liu
Zheng Xiong
L. Zintgraf
Chelsea Finn
Shimon Whiteson
OOD
OffRL
37
122
0
19 Jan 2023
Human-Timescale Adaptation in an Open-Ended Task Space
Human-Timescale Adaptation in an Open-Ended Task Space
Adaptive Agent Team
Jakob Bauer
Kate Baumli
Satinder Baveja
Feryal M. P. Behbahani
...
Jakub Sygnowski
K. Tuyls
Sarah York
Alexander Zacherl
Lei Zhang
LM&Ro
OffRL
AI4CE
LRM
38
109
0
18 Jan 2023
Knowing the Past to Predict the Future: Reinforcement Virtual Learning
Knowing the Past to Predict the Future: Reinforcement Virtual Learning
Peng Zhang
Yawen Huang
Bingzhang Hu
Shizheng Wang
Haoran Duan
Noura Al Moubayed
Yefeng Zheng
Yang Long
OffRL
27
0
0
02 Nov 2022
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on
  Continual Learning and Functional Composition
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition
Jorge Armando Mendez Mendez
Eric Eaton
KELM
CLL
32
27
0
15 Jul 2022
Reactive Exploration to Cope with Non-Stationarity in Lifelong
  Reinforcement Learning
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
C. Steinparz
Thomas Schmied
Fabian Paischer
Marius-Constantin Dinu
Vihang Patil
Angela Bitto-Nemling
Hamid Eghbalzadeh
Sepp Hochreiter
CLL
26
11
0
12 Jul 2022
Meta Reinforcement Learning with Finite Training Tasks -- a Density
  Estimation Approach
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach
Zohar Rimon
Aviv Tamar
Gilad Adler
OOD
OffRL
34
8
0
21 Jun 2022
Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward
  Machines
Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines
Xuejing Zheng
Chao Yu
Chong Chen
Jianye Hao
H. Zhuo
CLL
OffRL
17
9
0
18 Nov 2021
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative
  Survey
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey
Amjad Yousef Majid
Serge Saaybi
Tomas van Rietbergen
Vincent François-Lavet
R. V. Prasad
Chris Verhoeven
OffRL
62
54
0
28 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning
A Survey of Exploration Methods in Reinforcement Learning
Susan Amin
Maziar Gomrokchi
Harsh Satija
H. V. Hoof
Doina Precup
OffRL
26
80
0
01 Sep 2021
Lifelong Policy Gradient Learning of Factored Policies for Faster
  Training Without Forgetting
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
Jorge Armando Mendez Mendez
Boyu Wang
Eric Eaton
CLL
36
38
0
14 Jul 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
82
1,935
0
11 Apr 2020
Routing Networks and the Challenges of Modular and Compositional
  Computation
Routing Networks and the Challenges of Modular and Compositional Computation
Clemens Rosenbaum
Ignacio Cases
Matthew D Riemer
Tim Klinger
40
78
0
29 Apr 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
383
11,700
0
09 Mar 2017
1