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2406.14324
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Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics
20 June 2024
Charlotte Beylier
Simon M. Hofmann
Nico Scherf
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Papers citing
"Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics"
24 / 24 papers shown
Title
A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains
Minkyu Choi
Kuan Han
Xiaokai Wang
Yizhen Zhang
Zhongming Liu
66
14
0
20 Oct 2023
Machine versus Human Attention in Deep Reinforcement Learning Tasks
Sihang Guo
Ruohan Zhang
Bo Liu
Yifeng Zhu
M. Hayhoe
D. Ballard
Peter Stone
OffRL
66
27
0
29 Oct 2020
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future
Grace W. Lindsay
MedIm
91
432
0
20 Jan 2020
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution
Nikaash Puri
Sukriti Verma
Piyush B. Gupta
Dhruv Kayastha
Shripad Deshmukh
Balaji Krishnamurthy
Sameer Singh
FAtt
AAML
41
77
0
23 Dec 2019
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning
Akanksha Atrey
Kaleigh Clary
David D. Jensen
FAtt
LRM
61
91
0
09 Dec 2019
Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy
Aaron M. Roth
Nicholay Topin
Pooyan Jamshidi
Manuela Veloso
OffRL
54
48
0
02 Jul 2019
Explainable Reinforcement Learning Through a Causal Lens
Prashan Madumal
Tim Miller
L. Sonenberg
F. Vetere
CML
98
361
0
27 May 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
Sebastian Lapuschkin
S. Wäldchen
Alexander Binder
G. Montavon
Wojciech Samek
K. Müller
100
1,015
0
26 Feb 2019
Visual Rationalizations in Deep Reinforcement Learning for Atari Games
L. Weitkamp
Elise van der Pol
Zeynep Akata
48
27
0
01 Feb 2019
Quantifying Generalization in Reinforcement Learning
K. Cobbe
Oleg Klimov
Christopher Hesse
Taehoon Kim
John Schulman
OffRL
102
671
0
06 Dec 2018
Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences
J. V. D. Waa
J. Diggelen
K. Bosch
Mark Antonius Neerincx
OffRL
51
108
0
23 Jul 2018
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees
Guiliang Liu
Oliver Schulte
Wang Zhu
Qingcan Li
AI4CE
42
135
0
16 Jul 2018
Programmatically Interpretable Reinforcement Learning
Abhinav Verma
V. Murali
Rishabh Singh
Pushmeet Kohli
Swarat Chaudhuri
114
353
0
06 Apr 2018
Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning
Tianmin Shu
Caiming Xiong
R. Socher
OffRL
130
140
0
20 Dec 2017
Visualizing and Understanding Atari Agents
S. Greydanus
Anurag Koul
Jonathan Dodge
Alan Fern
FAtt
100
347
0
31 Oct 2017
Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies
D. Hein
A. Hentschel
Thomas Runkler
Steffen Udluft
OffRL
55
80
0
19 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
297
20,023
0
07 Oct 2016
Graying the black box: Understanding DQNs
Tom Zahavy
Nir Ben-Zrihem
Shie Mannor
84
263
0
08 Feb 2016
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
197
8,859
0
04 Feb 2016
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSL
SSeg
FAtt
250
9,319
0
14 Dec 2015
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition
G. Montavon
Sebastian Lapuschkin
Alexander Binder
Wojciech Samek
Klaus-Robert Muller
FAtt
60
737
0
08 Dec 2015
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
312
7,295
0
20 Dec 2013
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
127
12,231
0
19 Dec 2013
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
595
15,882
0
12 Nov 2013
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