Tarek R. Besold

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Artur d'Avila GarcezProfessor of Computer Science. City, University of LondonVerified email at city.ac.uk
Roberto ConfalonieriUniversity of Padova, Department of MathematicsVerified email at unipd.it
Luis LambComputer Science, AI, InnovationVerified email at mit.edu
Ute SchmidProfessor of Cognitive Systems, University of BambergVerified email at uni-bamberg.de
Tillman WeydeReader in Computer Science, City University LondonVerified email at city.ac.uk
Stephen MuggletonImperial College LondonVerified email at imperial.ac.uk
Pascal HitzlerLloyd T. Smith Creativity in Engineering Chair, Kansas State University, Manhattan, KansasVerified email at ksu.edu
Fermin Moscoso del Prado MartinUniversity of CambridgeVerified email at cam.ac.uk
Alireza Tamaddoni-NezhadReader (Associate Professor), University of SurreyVerified email at surrey.ac.uk
Lorijn ZaadnoordijkTrinity College Dublin, IrelandVerified email at tcd.ie
Leo de PenningIlluminooVerified email at illuminoo.com
Howard BowmanSchool of Psychology, University of BirminghamVerified email at bham.ac.uk
Gadi PinkasAfeka college of engineeringVerified email at afeka.ac.il
gerson zaveruchaProfessor, Universidade Federal do Rio de JaneiroVerified email at cos.ufrj.br
Sebastian BaderComputer Science, University of Rostock, GermanyVerified email at uni-rostock.de
Benedikt J. WagnerCity, University of LondonVerified email at city.ac.uk
Derek DoranDirector of Research, Tenet3; Associate Professor of Computer Science & Engineering, Wright StateVerified email at wright.edu
Risto MiikkulainenProfessor of Computer Science, the University of Texas at AustinVerified email at cs.utexas.edu
Maricarmen MartínezUniversidad de los AndesVerified email at uniandes.edu.co
Pedro DomingosProfessor of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu

Tarek R. Besold

Sony AI || Eindhoven University of Technology

Verified email at sony.com - Homepage

Artificial Intelligence Computational Creativity Trustworthy AI Cognitive Systems Neurosymbolic


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What does explainable AI really mean? A new conceptualization of perspectives D Doran arXiv preprint arXiv:1710.00794, 2017	751	2017
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	423*	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	360	2021
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	215	2015
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	129	2018
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	112	2021
Computational creativity research: towards creative machines TR Besold, M Schorlemmer, A Smaill Atlantis Press, 2015	80	2015
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	79*	2020
Lessons from infant learning for unsupervised machine learning L Zaadnoordijk, TR Besold, R Cusack Nature Machine Intelligence 4, 510-520, 2022	67*	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	54	2017
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	47	2015
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	33*	2023
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	32	2015
Generalize and blend: Concept blending based on generalization, analogy, and amalgams TR Besold, E Plaza	32	2015
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	29	2017
Concept invention R Confalonieri, A Pease, M Schorlemmer, TR Besold, O Kutz, E Maclean, ... Springer, 2018	28	2018
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	27	2019
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	26	2019
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	24	2017
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	23	2011

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