Theo dõi
Tarek R. Besold
Tarek R. Besold
Sony AI
Email được xác minh tại sony.com - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
What does explainable AI really mean? A new conceptualization of perspectives
D Doran, S Schulz, TR Besold
arXiv preprint arXiv:1710.00794, 2017
7912017
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
TR Besold, AA Garcez, S Bader, H Bowman, P Domingos, P Hitzler, ...
Neuro-Symbolic Artificial Intelligence: The State of the Art, 1-51, 2022
4772022
A historical perspective of explainable artificial intelligence
R Confalonieri, L Coba, B Wagner, TR Besold
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 11 (1 …, 2021
4262021
Neural-Symbolic Learning and Reasoning: Contributions and Challenges.
ASA Garcez, TR Besold, L De Raedt, P Földiak, P Hitzler, T Icard, ...
AAAI Spring Symposia, 18-21, 2015
2262015
Ultra-strong machine learning: comprehensibility of programs learned with ILP
SH Muggleton, U Schmid, C Zeller, A Tamaddoni-Nezhad, T Besold
Machine Learning 107, 1119-1140, 2018
1382018
Using ontologies to enhance human understandability of global post-hoc explanations of black-box models
R Confalonieri, T Weyde, TR Besold, FM del Prado Martín
Artificial Intelligence 296, 103471, 2021
1222021
Computational creativity research: towards creative machines
TR Besold, M Schorlemmer, A Smaill
Atlantis Press, 2015
912015
Trepan reloaded: A knowledge-driven approach to explaining black-box models
R Confalonieri, T Weyde, TR Besold, F Moscoso del Prado Martín
ECAI 2020, 2457-2464, 2020
83*2020
Lessons from infant learning for unsupervised machine learning
L Zaadnoordijk, TR Besold, R Cusack
Nature Machine Intelligence 4, 510-520, 2022
78*2022
How does predicate invention affect human comprehensibility?
U Schmid, C Zeller, T Besold, A Tamaddoni-Nezhad, S Muggleton
Inductive Logic Programming: 26th International Conference, ILP 2016, London …, 2017
552017
Towards integrated neural–symbolic systems for human-level AI: Two research programs helping to bridge the gaps
TR Besold, KU Kühnberger
Biologically Inspired Cognitive Architectures 14, 97-110, 2015
472015
Machine learning security in industry: A quantitative survey
K Grosse, L Bieringer, TR Besold, B Biggio, K Krombholz
IEEE Transactions on Information Forensics and Security 18, 1749-1762, 2023
43*2023
Reasoning in non-probabilistic uncertainty: Logic programming and neural-symbolic computing as examples
TR Besold, AA Garcez, K Stenning, L van der Torre, M van Lambalgen
Minds and Machines 27 (1), 37-77, 2017
342017
Can machine intelligence be measured in the same way as human intelligence?
T Besold, J Hernández-Orallo, U Schmid
KI-Künstliche Intelligenz 29, 291-297, 2015
332015
Generalize and blend: Concept blending based on generalization, analogy, and amalgams
TR Besold, E Plaza
322015
A match does not make a sense: on the sufficiency of the comparator model for explaining the sense of agency
L Zaadnoordijk, TR Besold, S Hunnius
Neuroscience of consciousness 2019 (1), niz006, 2019
302019
What makes a good explanation? Cognitive dimensions of explaining intelligent machines
R Confalonieri, TR Besold, T Weyde, K Creel, T Lombrozo, S Mueller, ...
Proceedings of the Annual Meeting of the Cognitive Science Society 41, 2019
282019
A narrative in three acts: Using combinations of image schemas to model events
TR Besold, MM Hedblom, O Kutz
Biologically inspired cognitive architectures 19, 10-20, 2017
282017
Concept invention
R Confalonieri, A Pease, M Schorlemmer, TR Besold, O Kutz, E Maclean, ...
Computational Synthesis and Creative Systems, 2018
272018
Towards a Domain-Independent Computational Framework for Theory Blending.
M Martinez, TR Besold, AMH Abdel-Fattah, KU Kuehnberger, H Gust, ...
AAAI Fall Symposium: Advances in Cognitive Systems, 210-217, 2011
242011
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