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Memory Sequence Length of Data Sampling Impacts the Adaptation of
  Meta-Reinforcement Learning Agents

Memory Sequence Length of Data Sampling Impacts the Adaptation of Meta-Reinforcement Learning Agents

18 June 2024
Menglong Zhang
Fuyuan Qian
Quanying Liu
ArXivPDFHTML

Papers citing "Memory Sequence Length of Data Sampling Impacts the Adaptation of Meta-Reinforcement Learning Agents"

4 / 4 papers shown
Title
FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization system
FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization system
Zeyuan Li
Yangfan He
Lewei He
Jianhui Wang
Tianyu Shi
Bin Lei
Yuchen Li
Qiuwu Chen
ALM
79
5
0
28 Oct 2024
Meta-Reinforcement Learning Based on Self-Supervised Task Representation
  Learning
Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning
Mingyang Wang
Zhenshan Bing
Xiangtong Yao
Shuai Wang
Hang Su
Chenguang Yang
Kai Huang
Alois C. Knoll
SSL
OOD
63
16
0
29 Apr 2023
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
196
640
0
19 Sep 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
496
11,727
0
09 Mar 2017
1