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Behaviour Discovery and Attribution for Explainable Reinforcement Learning
v1v2 (latest)

Behaviour Discovery and Attribution for Explainable Reinforcement Learning

19 March 2025
Rishav Rishav
Somjit Nath
Vincent Michalski
Samira Ebrahimi Kahou
    FAttOffRL
ArXiv (abs)PDFHTML

Papers citing "Behaviour Discovery and Attribution for Explainable Reinforcement Learning"

39 / 39 papers shown
Title
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning
Yuzheng Hu
Fan Wu
Haotian Ye
David A. Forsyth
James Y. Zou
Nan Jiang
Jiaqi W. Ma
Han Zhao
OffRL
49
0
0
25 May 2025
A Survey on Explainable Deep Reinforcement Learning
A Survey on Explainable Deep Reinforcement Learning
Zelei Cheng
Jiahao Yu
Masashi Sugiyama
OffRL
60
4
0
08 Feb 2025
RICE: Breaking Through the Training Bottlenecks of Reinforcement
  Learning with Explanation
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
Zelei Cheng
Xian Wu
Jiahao Yu
Sabrina Yang
Gang Wang
Xinyu Xing
OffRL
74
5
0
05 May 2024
Learning to Act without Actions
Learning to Act without Actions
Dominik Schmidt
Minqi Jiang
OffRL
109
38
0
17 Dec 2023
Action-Quantized Offline Reinforcement Learning for Robotic Skill
  Learning
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning
Jianlan Luo
Perry Dong
Jeffrey Wu
Aviral Kumar
Xinyang Geng
Sergey Levine
OffRL
98
23
0
18 Oct 2023
Accountability in Offline Reinforcement Learning: Explaining Decisions
  with a Corpus of Examples
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
Hao Sun
Alihan Huyuk
Daniel Jarrett
M. Schaar
OffRL
96
8
0
11 Oct 2023
Learning to Identify Critical States for Reinforcement Learning from
  Videos
Learning to Identify Critical States for Reinforcement Learning from Videos
Haozhe Liu
Mingchen Zhuge
Bing Li
Yu‐Han Wang
Francesco Faccio
Guohao Li
Jürgen Schmidhuber
OffRL
65
9
0
15 Aug 2023
Offline Skill Graph (OSG): A Framework for Learning and Planning using
  Offline Reinforcement Learning Skills
Offline Skill Graph (OSG): A Framework for Learning and Planning using Offline Reinforcement Learning Skills
Ben-ya Halevy
Y. Aperstein
Dotan Di Castro
GPOffRL
47
1
0
23 Jun 2023
Explaining Reinforcement Learning with Shapley Values
Explaining Reinforcement Learning with Shapley Values
Daniel Beechey
Thomas M. S. Smith
Özgür Simsek
TDIFAtt
54
18
0
09 Jun 2023
Explaining RL Decisions with Trajectories
Explaining RL Decisions with Trajectories
Shripad Deshmukh
Arpan Dasgupta
Balaji Krishnamurthy
Nan Jiang
Chirag Agarwal
Georgios Theocharous
J. Subramanian
OffRL
50
5
0
06 May 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges
Explainable Deep Reinforcement Learning: State of the Art and Challenges
G. Vouros
XAI
105
84
0
24 Jan 2023
Behavior Estimation from Multi-Source Data for Offline Reinforcement
  Learning
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning
Guoxi Zhang
H. Kashima
OffRL
55
2
0
29 Nov 2022
Offline Reinforcement Learning via High-Fidelity Generative Behavior
  Modeling
Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
Huayu Chen
Cheng Lu
Chengyang Ying
Hang Su
Jun Zhu
DiffMOffRL
176
122
0
29 Sep 2022
Planning with Diffusion for Flexible Behavior Synthesis
Planning with Diffusion for Flexible Behavior Synthesis
Michael Janner
Yilun Du
J. Tenenbaum
Sergey Levine
DiffM
318
702
0
20 May 2022
Bayesian Nonparametrics for Offline Skill Discovery
Bayesian Nonparametrics for Offline Skill Discovery
Valentin Villecroze
H. Braviner
Panteha Naderian
Chris J. Maddison
Gabriel Loaiza-Ganem
BDLOffRL
62
8
0
09 Feb 2022
The Option Keyboard: Combining Skills in Reinforcement Learning
The Option Keyboard: Combining Skills in Reinforcement Learning
André Barreto
Diana Borsa
Shaobo Hou
Gheorghe Comanici
Eser Aygun
...
Daniel Toyama
Jonathan J. Hunt
Shibl Mourad
David Silver
Doina Precup
61
99
0
24 Jun 2021
Causal Influence Detection for Improving Efficiency in Reinforcement
  Learning
Causal Influence Detection for Improving Efficiency in Reinforcement Learning
Maximilian Seitzer
Bernhard Schölkopf
Georg Martius
CML
91
78
0
07 Jun 2021
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement
  Learning
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay
Aviral Kumar
Pulkit Agrawal
Sergey Levine
Ofir Nachum
OffRLOnRL
90
159
0
26 Oct 2020
Explainable Deep Reinforcement Learning for UAV Autonomous Navigation
Explainable Deep Reinforcement Learning for UAV Autonomous Navigation
Lei He
Nabil Aouf
Bifeng Song
40
11
0
30 Sep 2020
Deep Structural Causal Models for Tractable Counterfactual Inference
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski
Daniel Coelho De Castro
Ben Glocker
CMLMedIm
108
243
0
11 Jun 2020
Local and Global Explanations of Agent Behavior: Integrating Strategy
  Summaries with Saliency Maps
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps
Tobias Huber
Katharina Weitz
Elisabeth André
Ofra Amir
FAtt
65
67
0
18 May 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Justin Fu
Aviral Kumar
Ofir Nachum
George Tucker
Sergey Levine
GPOffRL
237
1,384
0
15 Apr 2020
Explain Your Move: Understanding Agent Actions Using Specific and
  Relevant Feature Attribution
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
FAttAAML
50
79
0
23 Dec 2019
Dream to Control: Learning Behaviors by Latent Imagination
Dream to Control: Learning Behaviors by Latent Imagination
Danijar Hafner
Timothy Lillicrap
Jimmy Ba
Mohammad Norouzi
VLM
135
1,374
0
03 Dec 2019
Explainable Reinforcement Learning Through a Causal Lens
Explainable Reinforcement Learning Through a Causal Lens
Prashan Madumal
Tim Miller
L. Sonenberg
F. Vetere
CML
106
361
0
27 May 2019
Near-Optimal Representation Learning for Hierarchical Reinforcement
  Learning
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Ofir Nachum
S. Gu
Honglak Lee
Sergey Levine
73
211
0
02 Oct 2018
Transparency and Explanation in Deep Reinforcement Learning Neural
  Networks
Transparency and Explanation in Deep Reinforcement Learning Neural Networks
R. Iyer
Yuezhang Li
Huao Li
M. Lewis
R. Sundar
Katia Sycara
47
175
0
17 Sep 2018
Variational Option Discovery Algorithms
Variational Option Discovery Algorithms
Joshua Achiam
Harrison Edwards
Dario Amodei
Pieter Abbeel
DRL
72
180
0
26 Jul 2018
Programmatically Interpretable Reinforcement Learning
Programmatically Interpretable Reinforcement Learning
Abhinav Verma
V. Murali
Rishabh Singh
Pushmeet Kohli
Swarat Chaudhuri
130
355
0
06 Apr 2018
Diversity is All You Need: Learning Skills without a Reward Function
Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach
Abhishek Gupta
Julian Ibarz
Sergey Levine
113
1,089
0
16 Feb 2018
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDLSSLOCL
233
5,079
0
02 Nov 2017
Visualizing and Understanding Atari Agents
Visualizing and Understanding Atari Agents
S. Greydanus
Anurag Koul
Jonathan Dodge
Alan Fern
FAtt
114
348
0
31 Oct 2017
When Waiting is not an Option : Learning Options with a Deliberation
  Cost
When Waiting is not an Option : Learning Options with a Deliberation Cost
J. Harb
Pierre-Luc Bacon
Martin Klissarov
Doina Precup
55
149
0
14 Sep 2017
A Brief Survey of Deep Reinforcement Learning
A Brief Survey of Deep Reinforcement Learning
Kai Arulkumaran
M. Deisenroth
Miles Brundage
Anil Anthony Bharath
OffRL
133
2,830
0
19 Aug 2017
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
547
19,296
0
20 Jul 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,090
0
22 May 2017
The Option-Critic Architecture
The Option-Critic Architecture
Pierre-Luc Bacon
J. Harb
Doina Precup
OffRL
71
1,089
0
16 Sep 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
Graying the black box: Understanding DQNs
Graying the black box: Understanding DQNs
Tom Zahavy
Nir Ben-Zrihem
Shie Mannor
84
263
0
08 Feb 2016
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