Counterfactual state explanations for reinforcement learning agents via generative deep learning-Reference-Cited by-同舟云学术

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Counterfactual state explanations for reinforcement learning agents via generative deep learning

Published:2021-06 Issue: Volume:295 Page:103455
ISSN:0004-3702
Container-title:Artificial Intelligence
language:en
Short-container-title:Artificial Intelligence

Author:

Olson Matthew L.^ORCID,Khanna Roli,Neal Lawrence,Li Fuxin^ORCID,Wong Weng-Keen^ORCID

Funder

Defense Advanced Research Projects Agency

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference64 articles.

1. Sanity checks for saliency maps;Adebayo,2018

2. Autoencoder-augmented neuroevolution for visual doom playing;Alvernaz,2017

3. Highlights: summarizing agent behavior to people;Amir,2018

4. Mental models of mere mortals with explanations of reinforcement learning;Anderson;ACM Trans. Interact. Intell. Syst.,2020

5. Exploratory not explanatory: counterfactual analysis of saliency maps for deep reinforcement learning;Atrey,2020

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3. XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review;ACM Computing Surveys;2024-07-09

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