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Efficient Open-world Reinforcement Learning via Knowledge Distillation
  and Autonomous Rule Discovery

Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery

24 November 2023
Ekaterina Nikonova
Cheng Xue
Jochen Renz
    CLL
ArXivPDFHTML

Papers citing "Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery"

6 / 6 papers shown
Title
Collaborative Knowledge Distillation via a Learning-by-Education Node
  Community
Collaborative Knowledge Distillation via a Learning-by-Education Node Community
Anestis Kaimakamidis
Ioannis Mademlis
Ioannis Pitas
30
0
0
30 Sep 2024
RAPid-Learn: A Framework for Learning to Recover for Handling Novelties
  in Open-World Environments
RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World Environments
Shivam Goel
Yash Shukla
Vasanth Sarathy
matthias. scheutz
Jivko Sinapov
38
15
0
24 Jun 2022
A Review of Safe Reinforcement Learning: Methods, Theory and
  Applications
A Review of Safe Reinforcement Learning: Methods, Theory and Applications
Shangding Gu
Longyu Yang
Yali Du
Guang Chen
Florian Walter
Jun Wang
Alois C. Knoll
OffRL
AI4TS
115
237
0
20 May 2022
Curriculum Learning for Reinforcement Learning Domains: A Framework and
  Survey
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar
Bei Peng
Matteo Leonetti
Jivko Sinapov
Matthew E. Taylor
Peter Stone
ODL
152
458
0
10 Mar 2020
StarCraft Micromanagement with Reinforcement Learning and Curriculum
  Transfer Learning
StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer Learning
Kun Shao
Yuanheng Zhu
Dongbin Zhao
107
170
0
03 Apr 2018
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
332
11,684
0
09 Mar 2017
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