A systematic review of human-centered explainability in reinforcement learning. Transferring the RCC framework to support epistemic trustworthiness
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985955%3A_____%2F25%3A00639875" target="_blank" >RIV/67985955:_____/25:00639875 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s42454-025-00084-w" target="_blank" >https://doi.org/10.1007/s42454-025-00084-w</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s42454-025-00084-w" target="_blank" >10.1007/s42454-025-00084-w</a>
Alternative languages
Result language
angličtina
Original language name
A systematic review of human-centered explainability in reinforcement learning. Transferring the RCC framework to support epistemic trustworthiness
Original language description
This paper presents a systematic review of explainable reinforcement learning methodologies with an emphasis on human-centered evaluation frameworks. Drawing from literature between 2017 and 2025, we apply and extend the Reasons, Confidence, and Counterfactuals (RCC) Framework – originally designed for supervised learning – to reinforcement learning contexts. Our analysis reveals two predominant explanatory strategies: constructive, where explicit explanations are generated, and supportive, where users must infer reasoning from provided visual or textual cues. Our review also emphasizes human factor considerations, like task complexity, explanation formats, and evaluation methodologies. Particularly, for the latter, our analysis shows that improvement of the quality of decision is rarely measured.
Czech name
—
Czech description
—
Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
—
OECD FORD branch
60301 - Philosophy, History and Philosophy of science and technology
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Human-Intelligent Systems Integration
ISSN
2524-4876
e-ISSN
2524-4884
Volume of the periodical
7
Issue of the periodical within the volume
1
Country of publishing house
DE - GERMANY
Number of pages
10
Pages from-to
239-248
UT code for WoS article
—
EID of the result in the Scopus database
—