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Contrastive Explanations for Reinforcement Learning in terms of Expected
  Consequences

Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences

23 July 2018
J. V. D. Waa
J. Diggelen
K. Bosch
Mark Antonius Neerincx
    OffRL
ArXivPDFHTML

Papers citing "Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences"

26 / 26 papers shown
Title
Explainable Reinforcement Learning Agents Using World Models
Explainable Reinforcement Learning Agents Using World Models
Madhuri Singh
Amal Alabdulkarim
Gennie Mansi
Mark O. Riedl
24
0
0
12 May 2025
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics
Charlotte Beylier
Simon M. Hofmann
Nico Scherf
26
0
0
20 Jun 2024
Learning Interpretable Models of Aircraft Handling Behaviour by
  Reinforcement Learning from Human Feedback
Learning Interpretable Models of Aircraft Handling Behaviour by Reinforcement Learning from Human Feedback
Tom Bewley
J. Lawry
Arthur G. Richards
30
1
0
26 May 2023
A Human-Centered Safe Robot Reinforcement Learning Framework with
  Interactive Behaviors
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors
Shangding Gu
Alap Kshirsagar
Yali Du
Guang Chen
Jan Peters
Alois C. Knoll
34
14
0
25 Feb 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges
Explainable Deep Reinforcement Learning: State of the Art and Challenges
G. Vouros
XAI
50
77
0
24 Jan 2023
CEnt: An Entropy-based Model-agnostic Explainability Framework to
  Contrast Classifiers' Decisions
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions
Julia El Zini
Mohamad Mansour
M. Awad
33
1
0
19 Jan 2023
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
12
0
0
11 Nov 2022
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping
Ronilo Ragodos
Tong Wang
Qihang Lin
Xun Zhou
24
7
0
06 Nov 2022
Climate Change Policy Exploration using Reinforcement Learning
Climate Change Policy Exploration using Reinforcement Learning
Theodore Wolf
23
0
0
23 Oct 2022
Redefining Counterfactual Explanations for Reinforcement Learning:
  Overview, Challenges and Opportunities
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities
Jasmina Gajcin
Ivana Dusparic
CML
OffRL
35
8
0
21 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
38
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
Explainability in reinforcement learning: perspective and position
Explainability in reinforcement learning: perspective and position
Agneza Krajna
Mario Brčič
T. Lipić
Juraj Dončević
34
27
0
22 Mar 2022
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement
  Learning
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning
Jasmina Gajcin
Ivana Dusparic
CML
45
6
0
21 Mar 2022
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework
  and Survey
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey
Richard Dazeley
Peter Vamplew
Francisco Cruz
32
59
0
20 Aug 2021
Explainable Autonomous Robots: A Survey and Perspective
Explainable Autonomous Robots: A Survey and Perspective
Tatsuya Sakai
Takayuki Nagai
20
67
0
06 May 2021
What Did You Think Would Happen? Explaining Agent Behaviour Through
  Intended Outcomes
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes
Herman Yau
Chris Russell
Simon Hadfield
FAtt
LRM
28
36
0
10 Nov 2020
Contrastive Explanations for Reinforcement Learning via Embedded Self
  Predictions
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin
Kim-Ho Lam
Alan Fern
SSL
22
24
0
11 Oct 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
21
64
0
18 May 2020
Self-Supervised Discovering of Interpretable Features for Reinforcement
  Learning
Self-Supervised Discovering of Interpretable Features for Reinforcement Learning
Wenjie Shi
Gao Huang
Shiji Song
Zhuoyuan Wang
Tingyu Lin
Cheng Wu
SSL
28
18
0
16 Mar 2020
The Emerging Landscape of Explainable AI Planning and Decision Making
The Emerging Landscape of Explainable AI Planning and Decision Making
Tathagata Chakraborti
S. Sreedharan
S. Kambhampati
27
112
0
26 Feb 2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for
  Sequential Decision-Making Problems with Inscrutable Representations
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations
S. Sreedharan
Utkarsh Soni
Mudit Verma
Siddharth Srivastava
S. Kambhampati
76
30
0
04 Feb 2020
Interestingness Elements for Explainable Reinforcement Learning:
  Understanding Agents' Capabilities and Limitations
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations
Pedro Sequeira
Melinda Gervasio
19
104
0
19 Dec 2019
Counterfactual States for Atari Agents via Generative Deep Learning
Counterfactual States for Atari Agents via Generative Deep Learning
Matthew Lyle Olson
Lawrence Neal
Fuxin Li
Weng-Keen Wong
CML
18
29
0
27 Sep 2019
Generating Counterfactual and Contrastive Explanations using SHAP
Generating Counterfactual and Contrastive Explanations using SHAP
Shubham Rathi
16
56
0
21 Jun 2019
Complementary reinforcement learning towards explainable agents
Complementary reinforcement learning towards explainable agents
J. H. Lee
13
12
0
01 Jan 2019
1