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Counterfactual State Explanations for Reinforcement Learning Agents via
  Generative Deep Learning

Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning

29 January 2021
Matthew Lyle Olson
Roli Khanna
Lawrence Neal
Fuxin Li
Weng-Keen Wong
    CML
ArXivPDFHTML

Papers citing "Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning"

13 / 13 papers shown
Title
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
Shahin Atakishiyev
Mohammad Salameh
Randy Goebel
72
6
0
18 Mar 2024
Global and Local Analysis of Interestingness for Competency-Aware Deep
  Reinforcement Learning
Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning
Pedro Sequeira
Jesse Hostetler
Melinda Gervasio
18
0
0
11 Nov 2022
Causal Explanation for Reinforcement Learning: Quantifying State and
  Temporal Importance
Causal Explanation for Reinforcement Learning: Quantifying State and Temporal Importance
Xiaoxiao Wang
Fanyu Meng
Xin Liu
Z. Kong
Xin Chen
XAI
CML
FAtt
42
4
0
24 Oct 2022
Experiential Explanations for Reinforcement Learning
Experiential Explanations for Reinforcement Learning
Amal Alabdulkarim
Madhuri Singh
Gennie Mansi
Kaely Hall
Mark O. Riedl
Mark O. Riedl
OffRL
43
3
0
10 Oct 2022
Measuring Interventional Robustness in Reinforcement Learning
Measuring Interventional Robustness in Reinforcement Learning
Katherine Avery
Jack Kenney
Pracheta Amaranath
Erica Cai
David D. Jensen
21
0
0
19 Sep 2022
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a
  Jointly Trained Generative Latent Space
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space
Eric Yeh
Pedro Sequeira
Jesse Hostetler
Melinda Gervasio
OOD
CML
BDL
OffRL
25
2
0
15 Jul 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic
  Models
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models
Xiaoting Shao
Kristian Kersting
BDL
22
1
0
16 May 2022
A Survey of Explainable Reinforcement Learning
A Survey of Explainable Reinforcement Learning
Stephanie Milani
Nicholay Topin
Manuela Veloso
Fei Fang
XAI
LRM
32
52
0
17 Feb 2022
If Only We Had Better Counterfactual Explanations: Five Key Deficits to
  Rectify in the Evaluation of Counterfactual XAI Techniques
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
Mark T. Keane
Eoin M. Kenny
Eoin Delaney
Barry Smyth
CML
27
146
0
26 Feb 2021
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
26
164
0
20 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and
  Adversarial Examples
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Timo Freiesleben
GAN
46
62
0
11 Sep 2020
Re-understanding Finite-State Representations of Recurrent Policy
  Networks
Re-understanding Finite-State Representations of Recurrent Policy Networks
Mohamad H. Danesh
Anurag Koul
Alan Fern
Saeed Khorram
31
21
0
06 Jun 2020
Semi-Supervised StyleGAN for Disentanglement Learning
Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie
Tero Karras
Animesh Garg
Shoubhik Debhath
Anjul Patney
Ankit B. Patel
Anima Anandkumar
DRL
89
72
0
06 Mar 2020
1