---
_id: '53228'
article_number: '106945'
author:
- first_name: Erfan Babaee
full_name: Tirkolaee, Erfan Babaee
last_name: Tirkolaee
- first_name: Ali Ebadi
full_name: Torkayesh, Ali Ebadi
last_name: Torkayesh
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Alireza
full_name: Goli, Alireza
last_name: Goli
- first_name: Vladimir
full_name: Simic, Vladimir
last_name: Simic
- first_name: Weiping
full_name: Ding, Weiping
last_name: Ding
citation:
ama: Tirkolaee EB, Torkayesh AE, Tavana M, Goli A, Simic V, Ding W. An integrated
decision support framework for resilient vaccine supply chain network design.
Engineering Applications of Artificial Intelligence. 2023;126. doi:10.1016/j.engappai.2023.106945
apa: Tirkolaee, E. B., Torkayesh, A. E., Tavana, M., Goli, A., Simic, V., &
Ding, W. (2023). An integrated decision support framework for resilient vaccine
supply chain network design. Engineering Applications of Artificial Intelligence,
126, Article 106945. https://doi.org/10.1016/j.engappai.2023.106945
bibtex: '@article{Tirkolaee_Torkayesh_Tavana_Goli_Simic_Ding_2023, title={An integrated
decision support framework for resilient vaccine supply chain network design},
volume={126}, DOI={10.1016/j.engappai.2023.106945},
number={106945}, journal={Engineering Applications of Artificial Intelligence},
publisher={Elsevier BV}, author={Tirkolaee, Erfan Babaee and Torkayesh, Ali Ebadi
and Tavana, Madjid and Goli, Alireza and Simic, Vladimir and Ding, Weiping}, year={2023}
}'
chicago: Tirkolaee, Erfan Babaee, Ali Ebadi Torkayesh, Madjid Tavana, Alireza Goli,
Vladimir Simic, and Weiping Ding. “An Integrated Decision Support Framework for
Resilient Vaccine Supply Chain Network Design.” Engineering Applications of
Artificial Intelligence 126 (2023). https://doi.org/10.1016/j.engappai.2023.106945.
ieee: 'E. B. Tirkolaee, A. E. Torkayesh, M. Tavana, A. Goli, V. Simic, and W. Ding,
“An integrated decision support framework for resilient vaccine supply chain network
design,” Engineering Applications of Artificial Intelligence, vol. 126,
Art. no. 106945, 2023, doi: 10.1016/j.engappai.2023.106945.'
mla: Tirkolaee, Erfan Babaee, et al. “An Integrated Decision Support Framework for
Resilient Vaccine Supply Chain Network Design.” Engineering Applications of
Artificial Intelligence, vol. 126, 106945, Elsevier BV, 2023, doi:10.1016/j.engappai.2023.106945.
short: E.B. Tirkolaee, A.E. Torkayesh, M. Tavana, A. Goli, V. Simic, W. Ding, Engineering
Applications of Artificial Intelligence 126 (2023).
date_created: 2024-04-04T13:59:47Z
date_updated: 2024-04-15T13:14:11Z
department:
- _id: '277'
doi: 10.1016/j.engappai.2023.106945
intvolume: ' 126'
keyword:
- Electrical and Electronic Engineering
- Artificial Intelligence
- Control and Systems Engineering
language:
- iso: eng
publication: Engineering Applications of Artificial Intelligence
publication_identifier:
issn:
- 0952-1976
publication_status: published
publisher: Elsevier BV
status: public
title: An integrated decision support framework for resilient vaccine supply chain
network design
type: journal_article
user_id: '51811'
volume: 126
year: '2023'
...
---
_id: '53230'
author:
- first_name: Hannan Amoozad
full_name: Mahdiraji, Hannan Amoozad
last_name: Mahdiraji
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Ali
full_name: Rezayar, Ali
last_name: Rezayar
citation:
ama: Mahdiraji HA, Tavana M, Rezayar A. A Game-Theoretic Framework for Analyzing
the Impact of Social Responsibility and Supply Chain Profitability. Cybernetics
and Systems. 2023;54(1):104-137. doi:10.1080/01969722.2022.2055402
apa: Mahdiraji, H. A., Tavana, M., & Rezayar, A. (2023). A Game-Theoretic Framework
for Analyzing the Impact of Social Responsibility and Supply Chain Profitability.
Cybernetics and Systems, 54(1), 104–137. https://doi.org/10.1080/01969722.2022.2055402
bibtex: '@article{Mahdiraji_Tavana_Rezayar_2023, title={A Game-Theoretic Framework
for Analyzing the Impact of Social Responsibility and Supply Chain Profitability},
volume={54}, DOI={10.1080/01969722.2022.2055402},
number={1}, journal={Cybernetics and Systems}, publisher={Informa UK Limited},
author={Mahdiraji, Hannan Amoozad and Tavana, Madjid and Rezayar, Ali}, year={2023},
pages={104–137} }'
chicago: 'Mahdiraji, Hannan Amoozad, Madjid Tavana, and Ali Rezayar. “A Game-Theoretic
Framework for Analyzing the Impact of Social Responsibility and Supply Chain Profitability.”
Cybernetics and Systems 54, no. 1 (2023): 104–37. https://doi.org/10.1080/01969722.2022.2055402.'
ieee: 'H. A. Mahdiraji, M. Tavana, and A. Rezayar, “A Game-Theoretic Framework for
Analyzing the Impact of Social Responsibility and Supply Chain Profitability,”
Cybernetics and Systems, vol. 54, no. 1, pp. 104–137, 2023, doi: 10.1080/01969722.2022.2055402.'
mla: Mahdiraji, Hannan Amoozad, et al. “A Game-Theoretic Framework for Analyzing
the Impact of Social Responsibility and Supply Chain Profitability.” Cybernetics
and Systems, vol. 54, no. 1, Informa UK Limited, 2023, pp. 104–37, doi:10.1080/01969722.2022.2055402.
short: H.A. Mahdiraji, M. Tavana, A. Rezayar, Cybernetics and Systems 54 (2023)
104–137.
date_created: 2024-04-04T14:01:48Z
date_updated: 2024-04-15T13:15:21Z
department:
- _id: '277'
doi: 10.1080/01969722.2022.2055402
intvolume: ' 54'
issue: '1'
keyword:
- Artificial Intelligence
- Information Systems
- Software
language:
- iso: eng
page: 104-137
publication: Cybernetics and Systems
publication_identifier:
issn:
- 0196-9722
- 1087-6553
publication_status: published
publisher: Informa UK Limited
status: public
title: A Game-Theoretic Framework for Analyzing the Impact of Social Responsibility
and Supply Chain Profitability
type: journal_article
user_id: '51811'
volume: 54
year: '2023'
...
---
_id: '53356'
author:
- first_name: Philipp
full_name: Terhörst, Philipp
id: '97123'
last_name: Terhörst
- first_name: Marco
full_name: Huber, Marco
last_name: Huber
- first_name: Naser
full_name: Damer, Naser
last_name: Damer
- first_name: Florian
full_name: Kirchbuchner, Florian
last_name: Kirchbuchner
- first_name: Kiran
full_name: Raja, Kiran
last_name: Raja
- first_name: Arjan
full_name: Kuijper, Arjan
last_name: Kuijper
citation:
ama: Terhörst P, Huber M, Damer N, Kirchbuchner F, Raja K, Kuijper A. Pixel-Level
Face Image Quality Assessment for Explainable Face Recognition. IEEE Transactions
on Biometrics, Behavior, and Identity Science. 2023;5(2):288-297. doi:10.1109/tbiom.2023.3263186
apa: Terhörst, P., Huber, M., Damer, N., Kirchbuchner, F., Raja, K., & Kuijper,
A. (2023). Pixel-Level Face Image Quality Assessment for Explainable Face Recognition.
IEEE Transactions on Biometrics, Behavior, and Identity Science, 5(2),
288–297. https://doi.org/10.1109/tbiom.2023.3263186
bibtex: '@article{Terhörst_Huber_Damer_Kirchbuchner_Raja_Kuijper_2023, title={Pixel-Level
Face Image Quality Assessment for Explainable Face Recognition}, volume={5}, DOI={10.1109/tbiom.2023.3263186},
number={2}, journal={IEEE Transactions on Biometrics, Behavior, and Identity Science},
publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Terhörst,
Philipp and Huber, Marco and Damer, Naser and Kirchbuchner, Florian and Raja,
Kiran and Kuijper, Arjan}, year={2023}, pages={288–297} }'
chicago: 'Terhörst, Philipp, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran
Raja, and Arjan Kuijper. “Pixel-Level Face Image Quality Assessment for Explainable
Face Recognition.” IEEE Transactions on Biometrics, Behavior, and Identity
Science 5, no. 2 (2023): 288–97. https://doi.org/10.1109/tbiom.2023.3263186.'
ieee: 'P. Terhörst, M. Huber, N. Damer, F. Kirchbuchner, K. Raja, and A. Kuijper,
“Pixel-Level Face Image Quality Assessment for Explainable Face Recognition,”
IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 5,
no. 2, pp. 288–297, 2023, doi: 10.1109/tbiom.2023.3263186.'
mla: Terhörst, Philipp, et al. “Pixel-Level Face Image Quality Assessment for Explainable
Face Recognition.” IEEE Transactions on Biometrics, Behavior, and Identity
Science, vol. 5, no. 2, Institute of Electrical and Electronics Engineers
(IEEE), 2023, pp. 288–97, doi:10.1109/tbiom.2023.3263186.
short: P. Terhörst, M. Huber, N. Damer, F. Kirchbuchner, K. Raja, A. Kuijper, IEEE
Transactions on Biometrics, Behavior, and Identity Science 5 (2023) 288–297.
date_created: 2024-04-08T09:33:24Z
date_updated: 2024-08-21T07:07:35Z
doi: 10.1109/tbiom.2023.3263186
intvolume: ' 5'
issue: '2'
keyword:
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Instrumentation
language:
- iso: eng
page: 288-297
publication: IEEE Transactions on Biometrics, Behavior, and Identity Science
publication_identifier:
issn:
- 2637-6407
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
type: journal_article
user_id: '97123'
volume: 5
year: '2023'
...
---
_id: '50262'
abstract:
- lang: eng
text: AbstractExplainable artificial intelligence
has mainly focused on static learning scenarios so far. We are interested in dynamic
scenarios where data is sampled progressively, and learning is done in an incremental
rather than a batch mode. We seek efficient incremental algorithms for computing
feature importance (FI). Permutation feature importance (PFI) is a well-established
model-agnostic measure to obtain global FI based on feature marginalization of
absent features. We propose an efficient, model-agnostic algorithm called iPFI
to estimate this measure incrementally and under dynamic modeling conditions including
concept drift. We prove theoretical guarantees on the approximation quality in
terms of expectation and variance. To validate our theoretical findings and the
efficacy of our approaches in incremental scenarios dealing with streaming data
rather than traditional batch settings, we conduct multiple experimental studies
on benchmark data with and without concept drift.
author:
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
citation:
ama: 'Fumagalli F, Muschalik M, Hüllermeier E, Hammer B. Incremental permutation
feature importance (iPFI): towards online explanations on data streams. Machine
Learning. 2023;112(12):4863-4903. doi:10.1007/s10994-023-06385-y'
apa: 'Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). Incremental
permutation feature importance (iPFI): towards online explanations on data streams.
Machine Learning, 112(12), 4863–4903. https://doi.org/10.1007/s10994-023-06385-y'
bibtex: '@article{Fumagalli_Muschalik_Hüllermeier_Hammer_2023, title={Incremental
permutation feature importance (iPFI): towards online explanations on data streams},
volume={112}, DOI={10.1007/s10994-023-06385-y},
number={12}, journal={Machine Learning}, publisher={Springer Science and Business
Media LLC}, author={Fumagalli, Fabian and Muschalik, Maximilian and Hüllermeier,
Eyke and Hammer, Barbara}, year={2023}, pages={4863–4903} }'
chicago: 'Fumagalli, Fabian, Maximilian Muschalik, Eyke Hüllermeier, and Barbara
Hammer. “Incremental Permutation Feature Importance (IPFI): Towards Online Explanations
on Data Streams.” Machine Learning 112, no. 12 (2023): 4863–4903. https://doi.org/10.1007/s10994-023-06385-y.'
ieee: 'F. Fumagalli, M. Muschalik, E. Hüllermeier, and B. Hammer, “Incremental permutation
feature importance (iPFI): towards online explanations on data streams,” Machine
Learning, vol. 112, no. 12, pp. 4863–4903, 2023, doi: 10.1007/s10994-023-06385-y.'
mla: 'Fumagalli, Fabian, et al. “Incremental Permutation Feature Importance (IPFI):
Towards Online Explanations on Data Streams.” Machine Learning, vol. 112,
no. 12, Springer Science and Business Media LLC, 2023, pp. 4863–903, doi:10.1007/s10994-023-06385-y.'
short: F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, Machine Learning 112
(2023) 4863–4903.
date_created: 2024-01-05T21:52:28Z
date_updated: 2025-01-16T16:20:12Z
department:
- _id: '660'
doi: 10.1007/s10994-023-06385-y
intvolume: ' 112'
issue: '12'
keyword:
- Artificial Intelligence
- Software
language:
- iso: eng
page: 4863-4903
project:
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
- _id: '109'
grant_number: '438445824'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: Machine Learning
publication_identifier:
issn:
- 0885-6125
- 1573-0565
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: 'Incremental permutation feature importance (iPFI): towards online explanations
on data streams'
type: journal_article
user_id: '93420'
volume: 112
year: '2023'
...
---
_id: '48678'
abstract:
- lang: eng
text: Explanation has been identified as an important capability for AI-based
systems, but research on systematic strategies for achieving understanding in
interaction with such systems is still sparse. Negation is a linguistic strategy
that is often used in explanations. It creates a contrast space between the affirmed
and the negated item that enriches explaining processes with additional contextual
information. While negation in human speech has been shown to lead to higher processing
costs and worse task performance in terms of recall or action execution when used
in isolation, it can decrease processing costs when used in context. So far, it
has not been considered as a guiding strategy for explanations in human-robot
interaction. We conducted an empirical study to investigate the use of negation
as a guiding strategy in explanatory human-robot dialogue, in which a virtual
robot explains tasks and possible actions to a human explainee to solve them in
terms of gestures on a touchscreen. Our results show that negation vs. affirmation
1) increases processing costs measured as reaction time and 2) increases several
aspects of task performance. While there was no significant effect of negation
on the number of initially correctly executed gestures, we found a significantly
lower number of attempts—measured as breaks in the finger movement data before
the correct gesture was carried out—when being instructed through a negation.
We further found that the gestures significantly resembled the presented prototype
gesture more following an instruction with a negation as opposed to an affirmation.
Also, the participants rated the benefit of contrastive vs. affirmative explanations
significantly higher. Repeating the instructions decreased the effects of negation,
yielding similar processing costs and task performance measures for negation and
affirmation after several iterations. We discuss our results with respect to possible
effects of negation on linguistic processing of explanations and limitations of
our study.
author:
- first_name: André
full_name: Groß, André
last_name: Groß
- first_name: Amit
full_name: Singh, Amit
last_name: Singh
- first_name: Ngoc Chi
full_name: Banh, Ngoc Chi
last_name: Banh
- first_name: Birte
full_name: Richter, Birte
last_name: Richter
- first_name: Ingrid
full_name: Scharlau, Ingrid
last_name: Scharlau
- first_name: Katharina J.
full_name: Rohlfing, Katharina J.
last_name: Rohlfing
- first_name: Britta
full_name: Wrede, Britta
last_name: Wrede
citation:
ama: Groß A, Singh A, Banh NC, et al. Scaffolding the human partner by contrastive
guidance in an explanatory human-robot dialogue. Frontiers in Robotics and
AI. 2023;10. doi:10.3389/frobt.2023.1236184
apa: Groß, A., Singh, A., Banh, N. C., Richter, B., Scharlau, I., Rohlfing, K. J.,
& Wrede, B. (2023). Scaffolding the human partner by contrastive guidance
in an explanatory human-robot dialogue. Frontiers in Robotics and AI, 10.
https://doi.org/10.3389/frobt.2023.1236184
bibtex: '@article{Groß_Singh_Banh_Richter_Scharlau_Rohlfing_Wrede_2023, title={Scaffolding
the human partner by contrastive guidance in an explanatory human-robot dialogue},
volume={10}, DOI={10.3389/frobt.2023.1236184},
journal={Frontiers in Robotics and AI}, publisher={Frontiers Media SA}, author={Groß,
André and Singh, Amit and Banh, Ngoc Chi and Richter, Birte and Scharlau, Ingrid
and Rohlfing, Katharina J. and Wrede, Britta}, year={2023} }'
chicago: Groß, André, Amit Singh, Ngoc Chi Banh, Birte Richter, Ingrid Scharlau,
Katharina J. Rohlfing, and Britta Wrede. “Scaffolding the Human Partner by Contrastive
Guidance in an Explanatory Human-Robot Dialogue.” Frontiers in Robotics and
AI 10 (2023). https://doi.org/10.3389/frobt.2023.1236184.
ieee: 'A. Groß et al., “Scaffolding the human partner by contrastive guidance
in an explanatory human-robot dialogue,” Frontiers in Robotics and AI,
vol. 10, 2023, doi: 10.3389/frobt.2023.1236184.'
mla: Groß, André, et al. “Scaffolding the Human Partner by Contrastive Guidance
in an Explanatory Human-Robot Dialogue.” Frontiers in Robotics and AI,
vol. 10, Frontiers Media SA, 2023, doi:10.3389/frobt.2023.1236184.
short: A. Groß, A. Singh, N.C. Banh, B. Richter, I. Scharlau, K.J. Rohlfing, B.
Wrede, Frontiers in Robotics and AI 10 (2023).
date_created: 2023-11-08T06:40:41Z
date_updated: 2025-09-11T10:32:44Z
doi: 10.3389/frobt.2023.1236184
intvolume: ' 10'
keyword:
- Artificial Intelligence
- Computer Science Applications
publication: Frontiers in Robotics and AI
publication_identifier:
issn:
- 2296-9144
publication_status: published
publisher: Frontiers Media SA
status: public
title: Scaffolding the human partner by contrastive guidance in an explanatory human-robot
dialogue
type: journal_article
user_id: '93405'
volume: 10
year: '2023'
...
---
_id: '27506'
abstract:
- lang: eng
text: Explainability for machine learning gets more and more important in high-stakes
decisions like real estate appraisal. While traditional hedonic house pricing
models are fed with hard information based on housing attributes, recently also
soft information has been incorporated to increase the predictive performance.
This soft information can be extracted from image data by complex models like
Convolutional Neural Networks (CNNs). However, these are intransparent which excludes
their use for high-stakes financial decisions. To overcome this limitation, we
examine if a two-stage modeling approach can provide explainability. We combine
visual interpretability by Regression Activation Maps (RAM) for the CNN and a
linear regression for the overall prediction. Our experiments are based on 62.000
family homes in Philadelphia and the results indicate that the CNN learns aspects
related to vegetation and quality aspects of the house from exterior images, improving
the predictive accuracy of real estate appraisal by up to 5.4%.
author:
- first_name: Jan-Peter
full_name: Kucklick, Jan-Peter
id: '77066'
last_name: Kucklick
citation:
ama: 'Kucklick J-P. Visual Interpretability of Image-based Real Estate Appraisal.
In: 55th Annual Hawaii International Conference on System Sciences (HICSS-55).
; 2022.'
apa: Kucklick, J.-P. (2022). Visual Interpretability of Image-based Real Estate
Appraisal. 55th Annual Hawaii International Conference on System Sciences (HICSS-55).
Hawaii International Conference on System Science (HICSS), Virtual.
bibtex: '@inproceedings{Kucklick_2022, title={Visual Interpretability of Image-based
Real Estate Appraisal}, booktitle={55th Annual Hawaii International Conference
on System Sciences (HICSS-55)}, author={Kucklick, Jan-Peter}, year={2022} }'
chicago: Kucklick, Jan-Peter. “Visual Interpretability of Image-Based Real Estate
Appraisal.” In 55th Annual Hawaii International Conference on System Sciences
(HICSS-55), 2022.
ieee: J.-P. Kucklick, “Visual Interpretability of Image-based Real Estate Appraisal,”
presented at the Hawaii International Conference on System Science (HICSS), Virtual,
2022.
mla: Kucklick, Jan-Peter. “Visual Interpretability of Image-Based Real Estate Appraisal.”
55th Annual Hawaii International Conference on System Sciences (HICSS-55),
2022.
short: 'J.-P. Kucklick, in: 55th Annual Hawaii International Conference on System
Sciences (HICSS-55), 2022.'
conference:
end_date: 2022-01-07
location: Virtual
name: Hawaii International Conference on System Science (HICSS)
start_date: 2022-01-03
date_created: 2021-11-17T07:08:15Z
date_updated: 2022-01-06T06:57:40Z
department:
- _id: '195'
- _id: '196'
keyword:
- Explainable Artificial Intelligence (XAI)
- Regression Activation Maps
- Real Estate Appraisal
- Convolutional Block Attention Module
- Computer Vision
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://scholarspace.manoa.hawaii.edu/bitstream/10125/79519/0149.pdf
oa: '1'
publication: 55th Annual Hawaii International Conference on System Sciences (HICSS-55)
status: public
title: Visual Interpretability of Image-based Real Estate Appraisal
type: conference
user_id: '77066'
year: '2022'
...
---
_id: '29539'
abstract:
- lang: eng
text: Explainable Artificial Intelligence (XAI) is currently an important topic
for the application of Machine Learning (ML) in high-stakes decision scenarios.
Related research focuses on evaluating ML algorithms in terms of interpretability.
However, providing a human understandable explanation of an intelligent system
does not only relate to the used ML algorithm. The data and features used also
have a considerable impact on interpretability. In this paper, we develop a taxonomy
for describing XAI systems based on aspects about the algorithm and data. The
proposed taxonomy gives researchers and practitioners opportunities to describe
and evaluate current XAI systems with respect to interpretability and guides the
future development of this class of systems.
author:
- first_name: Jan-Peter
full_name: Kucklick, Jan-Peter
id: '77066'
last_name: Kucklick
citation:
ama: 'Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In:
Wirtschaftsinformatik 2022 Proceedings. ; 2022.'
apa: Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems.
Wirtschaftsinformatik 2022 Proceedings. Wirtschaftsinformatik 2022 (WI22),
Nürnberg (online).
bibtex: '@inproceedings{Kucklick_2022, title={Towards a model- and data-focused
taxonomy of XAI systems}, booktitle={Wirtschaftsinformatik 2022 Proceedings},
author={Kucklick, Jan-Peter}, year={2022} }'
chicago: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI
Systems.” In Wirtschaftsinformatik 2022 Proceedings, 2022.
ieee: J.-P. Kucklick, “Towards a model- and data-focused taxonomy of XAI systems,”
presented at the Wirtschaftsinformatik 2022 (WI22), Nürnberg (online), 2022.
mla: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.”
Wirtschaftsinformatik 2022 Proceedings, 2022.
short: 'J.-P. Kucklick, in: Wirtschaftsinformatik 2022 Proceedings, 2022.'
conference:
end_date: 2022-02-23
location: Nürnberg (online)
name: Wirtschaftsinformatik 2022 (WI22)
start_date: 2022-02-21
date_created: 2022-01-26T08:22:03Z
date_updated: 2022-01-26T08:24:30Z
department:
- _id: '195'
- _id: '196'
keyword:
- Explainable Artificial Intelligence
- XAI
- Interpretability
- Decision Support Systems
- Taxonomy
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1056&context=wi2022
oa: '1'
publication: Wirtschaftsinformatik 2022 Proceedings
status: public
title: Towards a model- and data-focused taxonomy of XAI systems
type: conference
user_id: '77066'
year: '2022'
...
---
_id: '30193'
abstract:
- lang: eng
text: The successful planning of future product generations requires reliable insights
into the actual products’ problems and potentials for improvement. A valuable
source for these insights is the product use phase. In practice, product planners
are often forced to work with assumptions and speculations as insights from the
use phase are insufficiently identified and documented. A new opportunity to address
this problem arises from the ongoing digitalization that enables products to generate
and collect data during their utilization. Analyzing these data could enable their
manufacturers to generate and exploit insights concerning product performance
and user behavior, revealing problems and potentials for improvement. However,
research on analyzing use phase data in product planning of manufacturing companies
is scarce. Therefore, we conducted an exploratory interview study with decision-makers
of eight manufacturing companies. The result of this paper is a detailed description
of the potentials and challenges that the interviewees associated with analyzing
use phase data in product planning. The potentials explain the intended purpose
and generic application examples. The challenges concern the products, the data,
the customers, the implementation, and the employees. By gathering the potentials
and challenges through expert interviews, our study structures the topic from
the perspective of the potential users and shows the needs for future research.
article_number: e14
author:
- first_name: Maurice
full_name: Meyer, Maurice
id: '77201'
last_name: Meyer
orcid: 0000-0003-0606-7321
- first_name: Timm
full_name: Fichtler, Timm
id: '66731'
last_name: Fichtler
- first_name: Christian
full_name: Koldewey, Christian
id: '43136'
last_name: Koldewey
orcid: https://orcid.org/0000-0001-7992-6399
- first_name: Roman
full_name: Dumitrescu, Roman
id: '16190'
last_name: Dumitrescu
citation:
ama: Meyer M, Fichtler T, Koldewey C, Dumitrescu R. Potentials and challenges of
analyzing use phase data in product planning of manufacturing companies. Artificial
Intelligence for Engineering Design, Analysis and Manufacturing. 2022;36.
doi:10.1017/s0890060421000408
apa: Meyer, M., Fichtler, T., Koldewey, C., & Dumitrescu, R. (2022). Potentials
and challenges of analyzing use phase data in product planning of manufacturing
companies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing,
36, Article e14. https://doi.org/10.1017/s0890060421000408
bibtex: '@article{Meyer_Fichtler_Koldewey_Dumitrescu_2022, title={Potentials and
challenges of analyzing use phase data in product planning of manufacturing companies},
volume={36}, DOI={10.1017/s0890060421000408},
number={e14}, journal={Artificial Intelligence for Engineering Design, Analysis
and Manufacturing}, publisher={Cambridge University Press (CUP)}, author={Meyer,
Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}, year={2022}
}'
chicago: Meyer, Maurice, Timm Fichtler, Christian Koldewey, and Roman Dumitrescu.
“Potentials and Challenges of Analyzing Use Phase Data in Product Planning of
Manufacturing Companies.” Artificial Intelligence for Engineering Design, Analysis
and Manufacturing 36 (2022). https://doi.org/10.1017/s0890060421000408.
ieee: 'M. Meyer, T. Fichtler, C. Koldewey, and R. Dumitrescu, “Potentials and challenges
of analyzing use phase data in product planning of manufacturing companies,” Artificial
Intelligence for Engineering Design, Analysis and Manufacturing, vol. 36,
Art. no. e14, 2022, doi: 10.1017/s0890060421000408.'
mla: Meyer, Maurice, et al. “Potentials and Challenges of Analyzing Use Phase Data
in Product Planning of Manufacturing Companies.” Artificial Intelligence for
Engineering Design, Analysis and Manufacturing, vol. 36, e14, Cambridge University
Press (CUP), 2022, doi:10.1017/s0890060421000408.
short: M. Meyer, T. Fichtler, C. Koldewey, R. Dumitrescu, Artificial Intelligence
for Engineering Design, Analysis and Manufacturing 36 (2022).
date_created: 2022-03-02T19:23:18Z
date_updated: 2022-10-19T12:29:54Z
department:
- _id: '563'
doi: 10.1017/s0890060421000408
intvolume: ' 36'
keyword:
- Artificial Intelligence
- Industrial and Manufacturing Engineering
language:
- iso: eng
publication: Artificial Intelligence for Engineering Design, Analysis and Manufacturing
publication_identifier:
issn:
- 0890-0604
- 1469-1760
publication_status: published
publisher: Cambridge University Press (CUP)
status: public
title: Potentials and challenges of analyzing use phase data in product planning of
manufacturing companies
type: journal_article
user_id: '15782'
volume: 36
year: '2022'
...
---
_id: '34046'
author:
- first_name: Christin
full_name: Hoffmann, Christin
last_name: Hoffmann
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
citation:
ama: Hoffmann C, Thommes K. Seizing the Opportunity for Automation—How Traffic Density
Determines Truck Drivers’ Use of Cruise Control. IEEE Transactions on Human-Machine
Systems. Published online 2022:1-11. doi:10.1109/thms.2022.3212335
apa: Hoffmann, C., & Thommes, K. (2022). Seizing the Opportunity for Automation—How
Traffic Density Determines Truck Drivers’ Use of Cruise Control. IEEE Transactions
on Human-Machine Systems, 1–11. https://doi.org/10.1109/thms.2022.3212335
bibtex: '@article{Hoffmann_Thommes_2022, title={Seizing the Opportunity for Automation—How
Traffic Density Determines Truck Drivers’ Use of Cruise Control}, DOI={10.1109/thms.2022.3212335},
journal={IEEE Transactions on Human-Machine Systems}, publisher={Institute of
Electrical and Electronics Engineers (IEEE)}, author={Hoffmann, Christin and Thommes,
Kirsten}, year={2022}, pages={1–11} }'
chicago: Hoffmann, Christin, and Kirsten Thommes. “Seizing the Opportunity for Automation—How
Traffic Density Determines Truck Drivers’ Use of Cruise Control.” IEEE Transactions
on Human-Machine Systems, 2022, 1–11. https://doi.org/10.1109/thms.2022.3212335.
ieee: 'C. Hoffmann and K. Thommes, “Seizing the Opportunity for Automation—How Traffic
Density Determines Truck Drivers’ Use of Cruise Control,” IEEE Transactions
on Human-Machine Systems, pp. 1–11, 2022, doi: 10.1109/thms.2022.3212335.'
mla: Hoffmann, Christin, and Kirsten Thommes. “Seizing the Opportunity for Automation—How
Traffic Density Determines Truck Drivers’ Use of Cruise Control.” IEEE Transactions
on Human-Machine Systems, Institute of Electrical and Electronics Engineers
(IEEE), 2022, pp. 1–11, doi:10.1109/thms.2022.3212335.
short: C. Hoffmann, K. Thommes, IEEE Transactions on Human-Machine Systems (2022)
1–11.
date_created: 2022-11-10T07:49:01Z
date_updated: 2023-01-09T14:05:54Z
department:
- _id: '178'
- _id: '184'
doi: 10.1109/thms.2022.3212335
keyword:
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Human-Computer Interaction
- Signal Processing
- Control and Systems Engineering
- Human Factors and Ergonomics
language:
- iso: eng
page: 1-11
publication: IEEE Transactions on Human-Machine Systems
publication_identifier:
issn:
- 2168-2291
- 2168-2305
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
quality_controlled: '1'
status: public
title: Seizing the Opportunity for Automation—How Traffic Density Determines Truck
Drivers' Use of Cruise Control
type: journal_article
user_id: '72497'
year: '2022'
...
---
_id: '44637'
article_number: '100258'
author:
- first_name: Julia Amelie
full_name: Hoppe, Julia Amelie
id: '73093'
last_name: Hoppe
- first_name: Outi
full_name: Tuisku, Outi
last_name: Tuisku
- first_name: Rose-Marie
full_name: Johansson-Pajala, Rose-Marie
last_name: Johansson-Pajala
- first_name: Satu
full_name: Pekkarinen, Satu
last_name: Pekkarinen
- first_name: Lea
full_name: Hennala, Lea
last_name: Hennala
- first_name: Christine
full_name: Gustafsson, Christine
last_name: Gustafsson
- first_name: Helinä
full_name: Melkas, Helinä
last_name: Melkas
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
citation:
ama: Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose
care robots over a human caregiver? Insights from a laboratory experiment on choices
under uncertainty. Computers in Human Behavior Reports. 2022;9. doi:10.1016/j.chbr.2022.100258
apa: Hoppe, J. A., Tuisku, O., Johansson-Pajala, R.-M., Pekkarinen, S., Hennala,
L., Gustafsson, C., Melkas, H., & Thommes, K. (2022). When do individuals
choose care robots over a human caregiver? Insights from a laboratory experiment
on choices under uncertainty. Computers in Human Behavior Reports, 9,
Article 100258. https://doi.org/10.1016/j.chbr.2022.100258
bibtex: '@article{Hoppe_Tuisku_Johansson-Pajala_Pekkarinen_Hennala_Gustafsson_Melkas_Thommes_2022,
title={When do individuals choose care robots over a human caregiver? Insights
from a laboratory experiment on choices under uncertainty}, volume={9}, DOI={10.1016/j.chbr.2022.100258},
number={100258}, journal={Computers in Human Behavior Reports}, publisher={Elsevier
BV}, author={Hoppe, Julia Amelie and Tuisku, Outi and Johansson-Pajala, Rose-Marie
and Pekkarinen, Satu and Hennala, Lea and Gustafsson, Christine and Melkas, Helinä
and Thommes, Kirsten}, year={2022} }'
chicago: Hoppe, Julia Amelie, Outi Tuisku, Rose-Marie Johansson-Pajala, Satu Pekkarinen,
Lea Hennala, Christine Gustafsson, Helinä Melkas, and Kirsten Thommes. “When Do
Individuals Choose Care Robots over a Human Caregiver? Insights from a Laboratory
Experiment on Choices under Uncertainty.” Computers in Human Behavior Reports
9 (2022). https://doi.org/10.1016/j.chbr.2022.100258.
ieee: 'J. A. Hoppe et al., “When do individuals choose care robots over a
human caregiver? Insights from a laboratory experiment on choices under uncertainty,”
Computers in Human Behavior Reports, vol. 9, Art. no. 100258, 2022, doi:
10.1016/j.chbr.2022.100258.'
mla: Hoppe, Julia Amelie, et al. “When Do Individuals Choose Care Robots over a
Human Caregiver? Insights from a Laboratory Experiment on Choices under Uncertainty.”
Computers in Human Behavior Reports, vol. 9, 100258, Elsevier BV, 2022,
doi:10.1016/j.chbr.2022.100258.
short: J.A. Hoppe, O. Tuisku, R.-M. Johansson-Pajala, S. Pekkarinen, L. Hennala,
C. Gustafsson, H. Melkas, K. Thommes, Computers in Human Behavior Reports 9 (2022).
date_created: 2023-05-08T12:28:18Z
date_updated: 2023-12-06T09:17:32Z
department:
- _id: '178'
- _id: '184'
doi: 10.1016/j.chbr.2022.100258
intvolume: ' 9'
keyword:
- Artificial Intelligence
- Cognitive Neuroscience
- Computer Science Applications
- Human-Computer Interaction
- Applied Psychology
- Neuroscience (miscellaneous)
language:
- iso: eng
project:
- _id: '46'
grant_number: 16SV7954
name: 'ORIENT: Use of care robots in welfare services: New models for effective
orientation'
publication: Computers in Human Behavior Reports
publication_identifier:
issn:
- 2451-9588
publication_status: published
publisher: Elsevier BV
status: public
title: When do individuals choose care robots over a human caregiver? Insights from
a laboratory experiment on choices under uncertainty
type: journal_article
user_id: '42933'
volume: 9
year: '2022'
...
---
_id: '34295'
article_number: '100258'
author:
- first_name: Julia Amelie
full_name: Hoppe, Julia Amelie
id: '73093'
last_name: Hoppe
- first_name: Outi
full_name: Tuisku, Outi
last_name: Tuisku
- first_name: Rose-Marie
full_name: Johansson-Pajala, Rose-Marie
last_name: Johansson-Pajala
- first_name: Satu
full_name: Pekkarinen, Satu
last_name: Pekkarinen
- first_name: Lea
full_name: Hennala, Lea
last_name: Hennala
- first_name: Christine
full_name: Gustafsson, Christine
last_name: Gustafsson
- first_name: Helinä
full_name: Melkas, Helinä
last_name: Melkas
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
citation:
ama: Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose
care robots over a human caregiver? Insights from a laboratory experiment on choices
under uncertainty. Computers in Human Behavior Reports. Published online
2022. doi:10.1016/j.chbr.2022.100258
apa: Hoppe, J. A., Tuisku, O., Johansson-Pajala, R.-M., Pekkarinen, S., Hennala,
L., Gustafsson, C., Melkas, H., & Thommes, K. (2022). When do individuals
choose care robots over a human caregiver? Insights from a laboratory experiment
on choices under uncertainty. Computers in Human Behavior Reports, Article
100258. https://doi.org/10.1016/j.chbr.2022.100258
bibtex: '@article{Hoppe_Tuisku_Johansson-Pajala_Pekkarinen_Hennala_Gustafsson_Melkas_Thommes_2022,
title={When do individuals choose care robots over a human caregiver? Insights
from a laboratory experiment on choices under uncertainty}, DOI={10.1016/j.chbr.2022.100258},
number={100258}, journal={Computers in Human Behavior Reports}, publisher={Elsevier
BV}, author={Hoppe, Julia Amelie and Tuisku, Outi and Johansson-Pajala, Rose-Marie
and Pekkarinen, Satu and Hennala, Lea and Gustafsson, Christine and Melkas, Helinä
and Thommes, Kirsten}, year={2022} }'
chicago: Hoppe, Julia Amelie, Outi Tuisku, Rose-Marie Johansson-Pajala, Satu Pekkarinen,
Lea Hennala, Christine Gustafsson, Helinä Melkas, and Kirsten Thommes. “When Do
Individuals Choose Care Robots over a Human Caregiver? Insights from a Laboratory
Experiment on Choices under Uncertainty.” Computers in Human Behavior Reports,
2022. https://doi.org/10.1016/j.chbr.2022.100258.
ieee: 'J. A. Hoppe et al., “When do individuals choose care robots over a
human caregiver? Insights from a laboratory experiment on choices under uncertainty,”
Computers in Human Behavior Reports, Art. no. 100258, 2022, doi: 10.1016/j.chbr.2022.100258.'
mla: Hoppe, Julia Amelie, et al. “When Do Individuals Choose Care Robots over a
Human Caregiver? Insights from a Laboratory Experiment on Choices under Uncertainty.”
Computers in Human Behavior Reports, 100258, Elsevier BV, 2022, doi:10.1016/j.chbr.2022.100258.
short: J.A. Hoppe, O. Tuisku, R.-M. Johansson-Pajala, S. Pekkarinen, L. Hennala,
C. Gustafsson, H. Melkas, K. Thommes, Computers in Human Behavior Reports (2022).
date_created: 2022-12-09T08:08:57Z
date_updated: 2023-12-06T09:18:14Z
department:
- _id: '178'
- _id: '184'
doi: 10.1016/j.chbr.2022.100258
keyword:
- Artificial Intelligence
- Cognitive Neuroscience
- Computer Science Applications
- Human-Computer Interaction
- Applied Psychology
- Neuroscience (miscellaneous)
language:
- iso: eng
project:
- _id: '46'
grant_number: 16SV7954
name: 'ORIENT: Use of care robots in welfare services: New models for effective
orientation'
publication: Computers in Human Behavior Reports
publication_identifier:
issn:
- 2451-9588
publication_status: published
publisher: Elsevier BV
status: public
title: When do individuals choose care robots over a human caregiver? Insights from
a laboratory experiment on choices under uncertainty
type: journal_article
user_id: '42933'
year: '2022'
...
---
_id: '44636'
article_number: '100258'
author:
- first_name: Julia A.
full_name: Hoppe, Julia A.
last_name: Hoppe
- first_name: Outi
full_name: Tuisku, Outi
last_name: Tuisku
- first_name: Rose-Marie
full_name: Johansson-Pajala, Rose-Marie
last_name: Johansson-Pajala
- first_name: Satu
full_name: Pekkarinen, Satu
last_name: Pekkarinen
- first_name: Lea
full_name: Hennala, Lea
last_name: Hennala
- first_name: Christine
full_name: Gustafsson, Christine
last_name: Gustafsson
- first_name: Helinä
full_name: Melkas, Helinä
last_name: Melkas
- first_name: Kirsten
full_name: Thommes, Kirsten
last_name: Thommes
citation:
ama: Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose
care robots over a human caregiver? Insights from a laboratory experiment on choices
under uncertainty. Computers in Human Behavior Reports. 2022;9. doi:10.1016/j.chbr.2022.100258
apa: Hoppe, J. A., Tuisku, O., Johansson-Pajala, R.-M., Pekkarinen, S., Hennala,
L., Gustafsson, C., Melkas, H., & Thommes, K. (2022). When do individuals
choose care robots over a human caregiver? Insights from a laboratory experiment
on choices under uncertainty. Computers in Human Behavior Reports, 9,
Article 100258. https://doi.org/10.1016/j.chbr.2022.100258
bibtex: '@article{Hoppe_Tuisku_Johansson-Pajala_Pekkarinen_Hennala_Gustafsson_Melkas_Thommes_2022,
title={When do individuals choose care robots over a human caregiver? Insights
from a laboratory experiment on choices under uncertainty}, volume={9}, DOI={10.1016/j.chbr.2022.100258},
number={100258}, journal={Computers in Human Behavior Reports}, publisher={Elsevier
BV}, author={Hoppe, Julia A. and Tuisku, Outi and Johansson-Pajala, Rose-Marie
and Pekkarinen, Satu and Hennala, Lea and Gustafsson, Christine and Melkas, Helinä
and Thommes, Kirsten}, year={2022} }'
chicago: Hoppe, Julia A., Outi Tuisku, Rose-Marie Johansson-Pajala, Satu Pekkarinen,
Lea Hennala, Christine Gustafsson, Helinä Melkas, and Kirsten Thommes. “When Do
Individuals Choose Care Robots over a Human Caregiver? Insights from a Laboratory
Experiment on Choices under Uncertainty.” Computers in Human Behavior Reports
9 (2022). https://doi.org/10.1016/j.chbr.2022.100258.
ieee: 'J. A. Hoppe et al., “When do individuals choose care robots over a
human caregiver? Insights from a laboratory experiment on choices under uncertainty,”
Computers in Human Behavior Reports, vol. 9, Art. no. 100258, 2022, doi:
10.1016/j.chbr.2022.100258.'
mla: Hoppe, Julia A., et al. “When Do Individuals Choose Care Robots over a Human
Caregiver? Insights from a Laboratory Experiment on Choices under Uncertainty.”
Computers in Human Behavior Reports, vol. 9, 100258, Elsevier BV, 2022,
doi:10.1016/j.chbr.2022.100258.
short: J.A. Hoppe, O. Tuisku, R.-M. Johansson-Pajala, S. Pekkarinen, L. Hennala,
C. Gustafsson, H. Melkas, K. Thommes, Computers in Human Behavior Reports 9 (2022).
date_created: 2023-05-08T12:27:30Z
date_updated: 2023-12-06T09:17:55Z
department:
- _id: '178'
- _id: '184'
doi: 10.1016/j.chbr.2022.100258
intvolume: ' 9'
keyword:
- Artificial Intelligence
- Cognitive Neuroscience
- Computer Science Applications
- Human-Computer Interaction
- Applied Psychology
- Neuroscience (miscellaneous)
language:
- iso: eng
project:
- _id: '46'
grant_number: 16SV7954
name: 'ORIENT: Use of care robots in welfare services: New models for effective
orientation'
publication: Computers in Human Behavior Reports
publication_identifier:
issn:
- 2451-9588
publication_status: published
publisher: Elsevier BV
status: public
title: When do individuals choose care robots over a human caregiver? Insights from
a laboratory experiment on choices under uncertainty
type: journal_article
user_id: '42933'
volume: 9
year: '2022'
...
---
_id: '51348'
abstract:
- lang: eng
text: AbstractWith the perspective on applications
of AI-technology, especially data intensive deep learning approaches, the need
for methods to control and understand such models has been recognized and gave
rise to a new research domain labeled explainable artificial intelligence (XAI).
In this overview paper we give an interim appraisal of what has been achieved
so far and where there are still gaps in the research. We take an interdisciplinary
perspective to identify challenges on XAI research and point to open questions
with respect to the quality of the explanations regarding faithfulness and consistency
of explanations. On the other hand we see a need regarding the interaction between
XAI and user to allow for adaptability to specific information needs and explanatory
dialog for informed decision making as well as the possibility to correct models
and explanations by interaction. This endeavor requires an integrated interdisciplinary
perspective and rigorous approaches to empirical evaluation based on psychological,
linguistic and even sociological theories.
alternative_title:
- An Interdisciplinary Perspective
author:
- first_name: Ute
full_name: Schmid, Ute
last_name: Schmid
- first_name: Britta
full_name: Wrede, Britta
last_name: Wrede
citation:
ama: Schmid U, Wrede B. What is Missing in XAI So Far? KI - Künstliche Intelligenz.
2022;36(3-4):303-315. doi:10.1007/s13218-022-00786-2
apa: Schmid, U., & Wrede, B. (2022). What is Missing in XAI So Far? KI -
Künstliche Intelligenz, 36(3–4), 303–315. https://doi.org/10.1007/s13218-022-00786-2
bibtex: '@article{Schmid_Wrede_2022, title={What is Missing in XAI So Far?}, volume={36},
DOI={10.1007/s13218-022-00786-2},
number={3–4}, journal={KI - Künstliche Intelligenz}, publisher={Springer Science
and Business Media LLC}, author={Schmid, Ute and Wrede, Britta}, year={2022},
pages={303–315} }'
chicago: 'Schmid, Ute, and Britta Wrede. “What Is Missing in XAI So Far?” KI
- Künstliche Intelligenz 36, no. 3–4 (2022): 303–15. https://doi.org/10.1007/s13218-022-00786-2.'
ieee: 'U. Schmid and B. Wrede, “What is Missing in XAI So Far?,” KI - Künstliche
Intelligenz, vol. 36, no. 3–4, pp. 303–315, 2022, doi: 10.1007/s13218-022-00786-2.'
mla: Schmid, Ute, and Britta Wrede. “What Is Missing in XAI So Far?” KI - Künstliche
Intelligenz, vol. 36, no. 3–4, Springer Science and Business Media LLC, 2022,
pp. 303–15, doi:10.1007/s13218-022-00786-2.
short: U. Schmid, B. Wrede, KI - Künstliche Intelligenz 36 (2022) 303–315.
date_created: 2024-02-14T09:41:56Z
date_updated: 2024-02-26T08:48:49Z
department:
- _id: '660'
doi: 10.1007/s13218-022-00786-2
intvolume: ' 36'
issue: 3-4
keyword:
- Artificial Intelligence
language:
- iso: eng
page: 303-315
project:
- _id: '113'
name: 'TRR 318 - A3: TRR 318 - Subproject A3'
- _id: '115'
grant_number: '438445824'
name: 'TRR 318 - A05: TRR 318 - Echtzeitmessung der Aufmerksamkeit im Mensch-Roboter-Erklärdialog
(Teilprojekt A05)'
publication: KI - Künstliche Intelligenz
publication_identifier:
issn:
- 0933-1875
- 1610-1987
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: What is Missing in XAI So Far?
type: journal_article
user_id: '54779'
volume: 36
year: '2022'
...
---
_id: '51366'
author:
- first_name: Ute
full_name: Schmid, Ute
last_name: Schmid
- first_name: Britta
full_name: Wrede, Britta
last_name: Wrede
citation:
ama: Schmid U, Wrede B. Explainable AI. KI - Künstliche Intelligenz. 2022;36(3-4):207-210.
doi:10.1007/s13218-022-00788-0
apa: Schmid, U., & Wrede, B. (2022). Explainable AI. KI - Künstliche Intelligenz,
36(3–4), 207–210. https://doi.org/10.1007/s13218-022-00788-0
bibtex: '@article{Schmid_Wrede_2022, title={Explainable AI}, volume={36}, DOI={10.1007/s13218-022-00788-0},
number={3–4}, journal={KI - Künstliche Intelligenz}, publisher={Springer Science
and Business Media LLC}, author={Schmid, Ute and Wrede, Britta}, year={2022},
pages={207–210} }'
chicago: 'Schmid, Ute, and Britta Wrede. “Explainable AI.” KI - Künstliche Intelligenz
36, no. 3–4 (2022): 207–10. https://doi.org/10.1007/s13218-022-00788-0.'
ieee: 'U. Schmid and B. Wrede, “Explainable AI,” KI - Künstliche Intelligenz,
vol. 36, no. 3–4, pp. 207–210, 2022, doi: 10.1007/s13218-022-00788-0.'
mla: Schmid, Ute, and Britta Wrede. “Explainable AI.” KI - Künstliche Intelligenz,
vol. 36, no. 3–4, Springer Science and Business Media LLC, 2022, pp. 207–10, doi:10.1007/s13218-022-00788-0.
short: U. Schmid, B. Wrede, KI - Künstliche Intelligenz 36 (2022) 207–210.
date_created: 2024-02-18T10:03:11Z
date_updated: 2024-02-26T08:48:00Z
department:
- _id: '660'
doi: 10.1007/s13218-022-00788-0
intvolume: ' 36'
issue: 3-4
keyword:
- Artificial Intelligence
language:
- iso: eng
page: 207-210
project:
- _id: '113'
name: 'TRR 318 - A3: TRR 318 - Subproject A3'
- _id: '115'
grant_number: '438445824'
name: 'TRR 318 - A05: TRR 318 - Echtzeitmessung der Aufmerksamkeit im Mensch-Roboter-Erklärdialog
(Teilprojekt A05)'
publication: KI - Künstliche Intelligenz
publication_identifier:
issn:
- 0933-1875
- 1610-1987
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Explainable AI
type: journal_article
user_id: '54779'
volume: 36
year: '2022'
...
---
_id: '51365'
author:
- first_name: Britta
full_name: Wrede, Britta
last_name: Wrede
citation:
ama: 'Wrede B. AI: Back to the Roots? KI - Künstliche Intelligenz. 2022;36(2):117-120.
doi:10.1007/s13218-022-00773-7'
apa: 'Wrede, B. (2022). AI: Back to the Roots? KI - Künstliche Intelligenz,
36(2), 117–120. https://doi.org/10.1007/s13218-022-00773-7'
bibtex: '@article{Wrede_2022, title={AI: Back to the Roots?}, volume={36}, DOI={10.1007/s13218-022-00773-7},
number={2}, journal={KI - Künstliche Intelligenz}, publisher={Springer Science
and Business Media LLC}, author={Wrede, Britta}, year={2022}, pages={117–120}
}'
chicago: 'Wrede, Britta. “AI: Back to the Roots?” KI - Künstliche Intelligenz
36, no. 2 (2022): 117–20. https://doi.org/10.1007/s13218-022-00773-7.'
ieee: 'B. Wrede, “AI: Back to the Roots?,” KI - Künstliche Intelligenz, vol.
36, no. 2, pp. 117–120, 2022, doi: 10.1007/s13218-022-00773-7.'
mla: 'Wrede, Britta. “AI: Back to the Roots?” KI - Künstliche Intelligenz,
vol. 36, no. 2, Springer Science and Business Media LLC, 2022, pp. 117–20, doi:10.1007/s13218-022-00773-7.'
short: B. Wrede, KI - Künstliche Intelligenz 36 (2022) 117–120.
date_created: 2024-02-18T09:55:30Z
date_updated: 2024-02-26T08:50:19Z
department:
- _id: '660'
doi: 10.1007/s13218-022-00773-7
intvolume: ' 36'
issue: '2'
keyword:
- Artificial Intelligence
language:
- iso: eng
page: 117-120
project:
- _id: '113'
name: 'TRR 318 - A3: TRR 318 - Subproject A3'
publication: KI - Künstliche Intelligenz
publication_identifier:
issn:
- 0933-1875
- 1610-1987
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: 'AI: Back to the Roots?'
type: journal_article
user_id: '54779'
volume: 36
year: '2022'
...
---
_id: '52862'
author:
- first_name: Anni-Yasmin
full_name: Turhan, Anni-Yasmin
id: '104470'
last_name: Turhan
citation:
ama: 'Turhan A-Y. A Double Take at Conferences: The Hybrid Format. KI - Künstliche
Intelligenz. 2022;36(1):1-4. doi:10.1007/s13218-022-00758-6'
apa: 'Turhan, A.-Y. (2022). A Double Take at Conferences: The Hybrid Format. KI
- Künstliche Intelligenz, 36(1), 1–4. https://doi.org/10.1007/s13218-022-00758-6'
bibtex: '@article{Turhan_2022, title={A Double Take at Conferences: The Hybrid Format},
volume={36}, DOI={10.1007/s13218-022-00758-6},
number={1}, journal={KI - Künstliche Intelligenz}, publisher={Springer Science
and Business Media LLC}, author={Turhan, Anni-Yasmin}, year={2022}, pages={1–4}
}'
chicago: 'Turhan, Anni-Yasmin. “A Double Take at Conferences: The Hybrid Format.”
KI - Künstliche Intelligenz 36, no. 1 (2022): 1–4. https://doi.org/10.1007/s13218-022-00758-6.'
ieee: 'A.-Y. Turhan, “A Double Take at Conferences: The Hybrid Format,” KI -
Künstliche Intelligenz, vol. 36, no. 1, pp. 1–4, 2022, doi: 10.1007/s13218-022-00758-6.'
mla: 'Turhan, Anni-Yasmin. “A Double Take at Conferences: The Hybrid Format.” KI
- Künstliche Intelligenz, vol. 36, no. 1, Springer Science and Business Media
LLC, 2022, pp. 1–4, doi:10.1007/s13218-022-00758-6.'
short: A.-Y. Turhan, KI - Künstliche Intelligenz 36 (2022) 1–4.
date_created: 2024-03-25T14:00:30Z
date_updated: 2024-03-26T10:52:36Z
department:
- _id: '888'
doi: 10.1007/s13218-022-00758-6
intvolume: ' 36'
issue: '1'
keyword:
- Artificial Intelligence
language:
- iso: eng
page: 1-4
publication: KI - Künstliche Intelligenz
publication_identifier:
issn:
- 0933-1875
- 1610-1987
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: 'A Double Take at Conferences: The Hybrid Format'
type: journal_article
user_id: '9503'
volume: 36
year: '2022'
...
---
_id: '53236'
article_number: '117188'
author:
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Akram
full_name: Shaabani, Akram
last_name: Shaabani
- first_name: Debora
full_name: Di Caprio, Debora
last_name: Di Caprio
- first_name: Abbas
full_name: Bonyani, Abbas
last_name: Bonyani
citation:
ama: Tavana M, Shaabani A, Di Caprio D, Bonyani A. A novel Interval Type-2 Fuzzy
best-worst method and combined compromise solution for evaluating eco-friendly
packaging alternatives. Expert Systems with Applications. 2022;200. doi:10.1016/j.eswa.2022.117188
apa: Tavana, M., Shaabani, A., Di Caprio, D., & Bonyani, A. (2022). A novel
Interval Type-2 Fuzzy best-worst method and combined compromise solution for evaluating
eco-friendly packaging alternatives. Expert Systems with Applications,
200, Article 117188. https://doi.org/10.1016/j.eswa.2022.117188
bibtex: '@article{Tavana_Shaabani_Di Caprio_Bonyani_2022, title={A novel Interval
Type-2 Fuzzy best-worst method and combined compromise solution for evaluating
eco-friendly packaging alternatives}, volume={200}, DOI={10.1016/j.eswa.2022.117188},
number={117188}, journal={Expert Systems with Applications}, publisher={Elsevier
BV}, author={Tavana, Madjid and Shaabani, Akram and Di Caprio, Debora and Bonyani,
Abbas}, year={2022} }'
chicago: Tavana, Madjid, Akram Shaabani, Debora Di Caprio, and Abbas Bonyani. “A
Novel Interval Type-2 Fuzzy Best-Worst Method and Combined Compromise Solution
for Evaluating Eco-Friendly Packaging Alternatives.” Expert Systems with Applications
200 (2022). https://doi.org/10.1016/j.eswa.2022.117188.
ieee: 'M. Tavana, A. Shaabani, D. Di Caprio, and A. Bonyani, “A novel Interval Type-2
Fuzzy best-worst method and combined compromise solution for evaluating eco-friendly
packaging alternatives,” Expert Systems with Applications, vol. 200, Art.
no. 117188, 2022, doi: 10.1016/j.eswa.2022.117188.'
mla: Tavana, Madjid, et al. “A Novel Interval Type-2 Fuzzy Best-Worst Method and
Combined Compromise Solution for Evaluating Eco-Friendly Packaging Alternatives.”
Expert Systems with Applications, vol. 200, 117188, Elsevier BV, 2022,
doi:10.1016/j.eswa.2022.117188.
short: M. Tavana, A. Shaabani, D. Di Caprio, A. Bonyani, Expert Systems with Applications
200 (2022).
date_created: 2024-04-04T15:48:46Z
date_updated: 2024-04-15T13:16:05Z
department:
- _id: '277'
doi: 10.1016/j.eswa.2022.117188
intvolume: ' 200'
keyword:
- Artificial Intelligence
- Computer Science Applications
- General Engineering
language:
- iso: eng
publication: Expert Systems with Applications
publication_identifier:
issn:
- 0957-4174
publication_status: published
publisher: Elsevier BV
status: public
title: A novel Interval Type-2 Fuzzy best-worst method and combined compromise solution
for evaluating eco-friendly packaging alternatives
type: journal_article
user_id: '51811'
volume: 200
year: '2022'
...
---
_id: '45849'
abstract:
- lang: eng
text: 'AbstractDependence Logic was introduced
by Jouko Väänänen in 2007. We study a propositional variant of this logic(PDL)and
investigate a variety of parameterisations with respect to central decision problems.
The model checking problem (MC) ofPDLisNP-complete
(Ebbing and Lohmann, SOFSEM 2012). The subject of this research is to identify
a list of parameterisations (formula-size, formula-depth, treewidth, team-size,
number of variables) under which MC becomes fixed-parameter tractable. Furthermore,
we show that the number of disjunctions or the arity of dependence atoms (dep-arity)
as a parameter both yield a paraNP-completeness result. Then, we consider the
satisfiability problem (SAT) which classically is known to beNP-complete
as well (Lohmann and Vollmer, Studia Logica 2013). There we are presenting a different
picture: under team-size, or dep-arity SAT isparaNP-complete
whereas under all other mentioned parameters the problem isFPT.
Finally, we introduce a variant of the satisfiability problem, asking for a team
of a given size, and show for this problem an almost complete picture.'
author:
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Arne
full_name: Meier, Arne
last_name: Meier
citation:
ama: Mahmood Y, Meier A. Parameterised complexity of model checking and satisfiability
in propositional dependence logic. Annals of Mathematics and Artificial Intelligence.
2022;90(2-3):271-296. doi:10.1007/s10472-021-09730-w
apa: Mahmood, Y., & Meier, A. (2022). Parameterised complexity of model checking
and satisfiability in propositional dependence logic. Annals of Mathematics
and Artificial Intelligence, 90(2–3), 271–296. https://doi.org/10.1007/s10472-021-09730-w
bibtex: '@article{Mahmood_Meier_2022, title={Parameterised complexity of model checking
and satisfiability in propositional dependence logic}, volume={90}, DOI={10.1007/s10472-021-09730-w},
number={2–3}, journal={Annals of Mathematics and Artificial Intelligence}, publisher={Springer
Science and Business Media LLC}, author={Mahmood, Yasir and Meier, Arne}, year={2022},
pages={271–296} }'
chicago: 'Mahmood, Yasir, and Arne Meier. “Parameterised Complexity of Model Checking
and Satisfiability in Propositional Dependence Logic.” Annals of Mathematics
and Artificial Intelligence 90, no. 2–3 (2022): 271–96. https://doi.org/10.1007/s10472-021-09730-w.'
ieee: 'Y. Mahmood and A. Meier, “Parameterised complexity of model checking and
satisfiability in propositional dependence logic,” Annals of Mathematics and
Artificial Intelligence, vol. 90, no. 2–3, pp. 271–296, 2022, doi: 10.1007/s10472-021-09730-w.'
mla: Mahmood, Yasir, and Arne Meier. “Parameterised Complexity of Model Checking
and Satisfiability in Propositional Dependence Logic.” Annals of Mathematics
and Artificial Intelligence, vol. 90, no. 2–3, Springer Science and Business
Media LLC, 2022, pp. 271–96, doi:10.1007/s10472-021-09730-w.
short: Y. Mahmood, A. Meier, Annals of Mathematics and Artificial Intelligence 90
(2022) 271–296.
date_created: 2023-07-03T11:45:39Z
date_updated: 2024-06-04T16:06:59Z
doi: 10.1007/s10472-021-09730-w
extern: '1'
intvolume: ' 90'
issue: 2-3
keyword:
- Applied Mathematics
- Artificial Intelligence
language:
- iso: eng
page: 271-296
publication: Annals of Mathematics and Artificial Intelligence
publication_identifier:
issn:
- 1012-2443
- 1573-7470
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Parameterised complexity of model checking and satisfiability in propositional
dependence logic
type: journal_article
user_id: '99353'
volume: 90
year: '2022'
...
---
_id: '33684'
article_number: '102920'
author:
- first_name: Robert
full_name: Schade, Robert
id: '75963'
last_name: Schade
orcid: 0000-0002-6268-539
- first_name: Tobias
full_name: Kenter, Tobias
id: '3145'
last_name: Kenter
- first_name: Hossam
full_name: Elgabarty, Hossam
id: '60250'
last_name: Elgabarty
orcid: 0000-0002-4945-1481
- first_name: Michael
full_name: Lass, Michael
id: '24135'
last_name: Lass
orcid: 0000-0002-5708-7632
- first_name: Ole
full_name: Schütt, Ole
last_name: Schütt
- first_name: Alfio
full_name: Lazzaro, Alfio
last_name: Lazzaro
- first_name: Hans
full_name: Pabst, Hans
last_name: Pabst
- first_name: Stephan
full_name: Mohr, Stephan
last_name: Mohr
- first_name: Jürg
full_name: Hutter, Jürg
last_name: Hutter
- first_name: Thomas
full_name: Kühne, Thomas
id: '49079'
last_name: Kühne
- first_name: Christian
full_name: Plessl, Christian
id: '16153'
last_name: Plessl
orcid: 0000-0001-5728-9982
citation:
ama: Schade R, Kenter T, Elgabarty H, et al. Towards electronic structure-based
ab-initio molecular dynamics simulations with hundreds of millions of atoms. Parallel
Computing. 2022;111. doi:10.1016/j.parco.2022.102920
apa: Schade, R., Kenter, T., Elgabarty, H., Lass, M., Schütt, O., Lazzaro, A., Pabst,
H., Mohr, S., Hutter, J., Kühne, T., & Plessl, C. (2022). Towards electronic
structure-based ab-initio molecular dynamics simulations with hundreds of millions
of atoms. Parallel Computing, 111, Article 102920. https://doi.org/10.1016/j.parco.2022.102920
bibtex: '@article{Schade_Kenter_Elgabarty_Lass_Schütt_Lazzaro_Pabst_Mohr_Hutter_Kühne_et
al._2022, title={Towards electronic structure-based ab-initio molecular dynamics
simulations with hundreds of millions of atoms}, volume={111}, DOI={10.1016/j.parco.2022.102920},
number={102920}, journal={Parallel Computing}, publisher={Elsevier BV}, author={Schade,
Robert and Kenter, Tobias and Elgabarty, Hossam and Lass, Michael and Schütt,
Ole and Lazzaro, Alfio and Pabst, Hans and Mohr, Stephan and Hutter, Jürg and
Kühne, Thomas and et al.}, year={2022} }'
chicago: Schade, Robert, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt,
Alfio Lazzaro, Hans Pabst, et al. “Towards Electronic Structure-Based Ab-Initio
Molecular Dynamics Simulations with Hundreds of Millions of Atoms.” Parallel
Computing 111 (2022). https://doi.org/10.1016/j.parco.2022.102920.
ieee: 'R. Schade et al., “Towards electronic structure-based ab-initio molecular
dynamics simulations with hundreds of millions of atoms,” Parallel Computing,
vol. 111, Art. no. 102920, 2022, doi: 10.1016/j.parco.2022.102920.'
mla: Schade, Robert, et al. “Towards Electronic Structure-Based Ab-Initio Molecular
Dynamics Simulations with Hundreds of Millions of Atoms.” Parallel Computing,
vol. 111, 102920, Elsevier BV, 2022, doi:10.1016/j.parco.2022.102920.
short: R. Schade, T. Kenter, H. Elgabarty, M. Lass, O. Schütt, A. Lazzaro, H. Pabst,
S. Mohr, J. Hutter, T. Kühne, C. Plessl, Parallel Computing 111 (2022).
date_created: 2022-10-11T08:17:02Z
date_updated: 2023-08-02T15:03:55Z
department:
- _id: '613'
- _id: '27'
- _id: '518'
doi: 10.1016/j.parco.2022.102920
intvolume: ' 111'
keyword:
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design
- Computer Networks and Communications
- Hardware and Architecture
- Theoretical Computer Science
- Software
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.sciencedirect.com/science/article/pii/S0167819122000242
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Parallel Computing
publication_identifier:
issn:
- 0167-8191
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: Towards electronic structure-based ab-initio molecular dynamics simulations
with hundreds of millions of atoms
type: journal_article
user_id: '75963'
volume: 111
year: '2022'
...
---
_id: '48780'
abstract:
- lang: eng
text: Explainable Artificial Intelligence (XAI) has mainly focused on static learning
tasks so far. In this paper, we consider XAI in the context of online learning
in dynamic environments, such as learning from real-time data streams, where models
are learned incrementally and continuously adapted over the course of time. More
specifically, we motivate the problem of explaining model change, i.e. explaining
the difference between models before and after adaptation, instead of the models
themselves. In this regard, we provide the first efficient model-agnostic approach
to dynamically detecting, quantifying, and explaining significant model changes.
Our approach is based on an adaptation of the well-known Permutation Feature Importance
(PFI) measure. It includes two hyperparameters that control the sensitivity and
directly influence explanation frequency, so that a human user can adjust the
method to individual requirements and application needs. We assess and validate
our method’s efficacy on illustrative synthetic data streams with three popular
model classes.
author:
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Fabian
full_name: Fumagalli, Fabian
id: '93420'
last_name: Fumagalli
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Eyke
full_name: Huellermeier, Eyke
id: '48129'
last_name: Huellermeier
citation:
ama: Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Agnostic Explanation of
Model Change based on Feature Importance. KI - Künstliche Intelligenz.
2022;36(3-4):211-224. doi:10.1007/s13218-022-00766-6
apa: Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2022). Agnostic
Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz,
36(3–4), 211–224. https://doi.org/10.1007/s13218-022-00766-6
bibtex: '@article{Muschalik_Fumagalli_Hammer_Huellermeier_2022, title={Agnostic
Explanation of Model Change based on Feature Importance}, volume={36}, DOI={10.1007/s13218-022-00766-6},
number={3–4}, journal={KI - Künstliche Intelligenz}, publisher={Springer Science
and Business Media LLC}, author={Muschalik, Maximilian and Fumagalli, Fabian and
Hammer, Barbara and Huellermeier, Eyke}, year={2022}, pages={211–224} }'
chicago: 'Muschalik, Maximilian, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier.
“Agnostic Explanation of Model Change Based on Feature Importance.” KI - Künstliche
Intelligenz 36, no. 3–4 (2022): 211–24. https://doi.org/10.1007/s13218-022-00766-6.'
ieee: 'M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Agnostic Explanation
of Model Change based on Feature Importance,” KI - Künstliche Intelligenz,
vol. 36, no. 3–4, pp. 211–224, 2022, doi: 10.1007/s13218-022-00766-6.'
mla: Muschalik, Maximilian, et al. “Agnostic Explanation of Model Change Based on
Feature Importance.” KI - Künstliche Intelligenz, vol. 36, no. 3–4, Springer
Science and Business Media LLC, 2022, pp. 211–24, doi:10.1007/s13218-022-00766-6.
short: M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, KI - Künstliche Intelligenz
36 (2022) 211–224.
date_created: 2023-11-10T14:21:06Z
date_updated: 2025-01-16T16:19:35Z
department:
- _id: '660'
doi: 10.1007/s13218-022-00766-6
intvolume: ' 36'
issue: 3-4
keyword:
- Artificial Intelligence
language:
- iso: eng
page: 211-224
project:
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
- _id: '109'
grant_number: '438445824'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: KI - Künstliche Intelligenz
publication_identifier:
issn:
- 0933-1875
- 1610-1987
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Agnostic Explanation of Model Change based on Feature Importance
type: journal_article
user_id: '93420'
volume: 36
year: '2022'
...