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Tarek R. Besold
Tarek R. Besold
Sony AI || Eindhoven University of Technology
Verified email at sony.com - Homepage
Title
Cited by
Cited by
Year
What does explainable AI really mean? A new conceptualization of perspectives
D Doran, S Schulz, TR Besold
arXiv preprint arXiv:1710.00794, 2017
6232017
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
321*2022
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
2142021
Neural-symbolic learning and reasoning: contributions and challenges
AA Garcez, TR Besold, L De Raedt, P Földiak, P Hitzler, T Icard, ...
2015 AAAI Spring Symposium Series, 2015
1892015
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
1192018
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
742021
Computational creativity research: towards creative machines
TR Besold, M Schorlemmer, A Smaill
Atlantis Press, 2015
742015
Trepan reloaded: A knowledge-driven approach to explaining artificial neural networks
R Confalonieri, T Weyde, TR Besold, F Moscoso del Prado Martín
IOS Press 325, 2457-2464, 2020
62*2020
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
512017
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
432015
Lessons from infant learning for unsupervised machine learning
L Zaadnoordijk, TR Besold, R Cusack
Nature Machine Intelligence 4, 510-520, 2022
33*2022
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
322015
Generalize and blend: Concept blending based on generalization, analogy, and amalgams
TR Besold, E Plaza
312015
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, 37-77, 2017
302017
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
272019
Concept Invention
R Confalonieri, A Pease, M Schorlemmer, TR Besold, O Kutz, E Maclean, ...
Springer Nature, 2018
262018
Towards a domain-independent computational framework for theory blending
M Martinez, T Besold, A Abdel-Fattah, KU Kuehnberger, H Gust, ...
2011 AAAI Fall Symposium Series, 2011
242011
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
232017
What makes a good explanation? Cognitive dimensions of explaining intelligent machines.
R Confalonieri, TR Besold, T Weyde, K Creel, T Lombrozo, ST Mueller, ...
CogSci, 25-26, 2019
212019
An argument for an analogical perspective on rationality & decision-making
TR Besold, H Gust, U Krumnack, A Abdel-Fattah, M Schmidt, ...
Proceedings of the Workshop on Reasoning About Other Minds: Logical and …, 2011
182011
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