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Improving Performance in Reinforcement Learning by Breaking
  Generalization in Neural Networks

Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks

Adaptive Agents and Multi-Agent Systems (AAMAS), 2020
16 March 2020
Sina Ghiassian
Banafsheh Rafiee
Y. Lo
Adam White
ArXiv (abs)PDFHTML

Papers citing "Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks"

17 / 17 papers shown
Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions
Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions
Qingfeng Lan
Gautham Vasan
A. R. Mahmood
CLL
173
0
0
23 Sep 2025
Is Exploration or Optimization the Problem for Deep Reinforcement Learning?
Is Exploration or Optimization the Problem for Deep Reinforcement Learning?
Glen Berseth
OffRL
229
1
0
02 Aug 2025
LiBOG: Lifelong Learning for Black-Box Optimizer Generation
LiBOG: Lifelong Learning for Black-Box Optimizer GenerationInternational Joint Conference on Artificial Intelligence (IJCAI), 2025
Jiyuan Pei
Yi Mei
Jialin Liu
Mengjie Zhang
268
5
0
19 May 2025
Streaming Deep Reinforcement Learning Finally Works
Streaming Deep Reinforcement Learning Finally Works
Mohamed Elsayed
Gautham Vasan
A. R. Mahmood
OffRL
380
23
0
18 Oct 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of
  Value and Policy Churn
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy ChurnNeural Information Processing Systems (NeurIPS), 2024
Hongyao Tang
Glen Berseth
OffRL
372
12
0
07 Sep 2024
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
Augustine N. Mavor-Parker
Matthew J. Sargent
Caswell Barry
Lewis D. Griffin
Clare Lyle
502
4
0
09 Jul 2024
Harnessing Discrete Representations For Continual Reinforcement Learning
Harnessing Discrete Representations For Continual Reinforcement Learning
Edan Meyer
Adam White
Marlos C. Machado
OffRL
319
12
0
02 Dec 2023
Behavior Alignment via Reward Function Optimization
Behavior Alignment via Reward Function OptimizationNeural Information Processing Systems (NeurIPS), 2023
Dhawal Gupta
Yash Chandak
Scott M. Jordan
Philip S. Thomas
Bruno Castro da Silva
435
23
0
29 Oct 2023
Elephant Neural Networks: Born to Be a Continual Learner
Elephant Neural Networks: Born to Be a Continual Learner
Qingfeng Lan
A. Rupam Mahmood
CLL
469
11
0
02 Oct 2023
Improving generalization in reinforcement learning through forked agents
Improving generalization in reinforcement learning through forked agentsInternational Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE), 2022
Olivier Moulin
Vincent François-Lavet
Mark Hoogendoorn
AI4CE
356
0
0
13 Dec 2022
Reinforcement Learning with Automated Auxiliary Loss Search
Reinforcement Learning with Automated Auxiliary Loss SearchNeural Information Processing Systems (NeurIPS), 2022
Tairan He
Yuge Zhang
Kan Ren
Minghuan Liu
Che Wang
Weinan Zhang
Yuqing Yang
Dongsheng Li
323
18
0
12 Oct 2022
Learning Dynamics and Generalization in Reinforcement Learning
Learning Dynamics and Generalization in Reinforcement Learning
Clare Lyle
Mark Rowland
Will Dabney
Marta Z. Kwiatkowska
Y. Gal
OODOffRL
238
17
0
05 Jun 2022
Memory-efficient Reinforcement Learning with Value-based Knowledge
  Consolidation
Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation
Qingfeng Lan
Yangchen Pan
Jun Luo
A. R. Mahmood
OffRL
599
10
0
22 May 2022
Improving generalization to new environments and removing catastrophic
  forgetting in Reinforcement Learning by using an eco-system of agents
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents
Olivier Moulin
Vincent François-Lavet
Paul Elbers
Mark Hoogendoorn
CLL
223
0
0
13 Apr 2022
Catastrophic Interference in Reinforcement Learning: A Solution Based on
  Context Division and Knowledge Distillation
Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge DistillationIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Tiantian Zhang
Xueqian Wang
Bin Liang
Bo Yuan
OffRL
220
24
0
01 Sep 2021
Does the Adam Optimizer Exacerbate Catastrophic Forgetting?
Does the Adam Optimizer Exacerbate Catastrophic Forgetting?
Dylan R. Ashley
Sina Ghiassian
R. Sutton
AAML
309
9
0
15 Feb 2021
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy
  Improvement
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement
Samuel Neumann
Sungsu Lim
A. Joseph
Yangchen Pan
Adam White
Martha White
564
13
0
22 Oct 2018
1
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