Items where Author is "Besold, T. R."
Article
Confalonieri, R., Weyde, T. 
ORCID: 0000-0001-8028-9905, Besold, T. R. & Moscoso del Prado Martín, F. (2021).
Using ontologies to enhance human understandability of global post-hoc explanations of black-box models.
Artificial Intelligence, 296,
article number 103471.
doi: 10.1016/j.artint.2021.103471
Confalonieri, R., Coba, L., Wagner, B. & Besold, T. R. (2021). A historical perspective of explainable Artificial Intelligence. WIREs Data Mining and Knowledge Discovery, 11(1), article number e1391. doi: 10.1002/widm.1391
Muggleton, S., Schmid, U., Zeller, C. , Tamaddoni-Nezhad, A. & Besold, T. R. ORCID: 0000-0002-8002-0049 (2018).
Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP.
Machine Learning, 107(7),
pp. 1119-1140.
doi: 10.1007/s10994-018-5707-3
Doran, D., Schulz, S.C. & Besold, T. R. (2018). What Does Explainable AI Really Mean? A New Conceptualization of Perspectives. CEUR Workshop Proceedings, 2071,
Besold, T. R. & Uckelman, S. L. (2018). The Normativity of Rationality: From Nature to Artifice and Back. Journal of Experimental and Theoretical Artificial Intelligence, 30(2), pp. 331-344. doi: 10.1080/0952813x.2018.1430860
Harder, F. & Besold, T. R. ORCID: 0000-0002-8002-0049 (2018).
Learning Lukasiewicz logic.
Cognitive Systems Research, 47,
pp. 42-67.
doi: 10.1016/j.cogsys.2017.07.004
Badra, F. & Besold, T. R. (2017). Preface. CEUR Workshop Proceedings, 2028, pp. 9-11.
Martinez, M., Abdel-Fattah, A. M. H., Krumnack, U. , Gomez-Ramirez, D., Smaill, A., Besold, T. R., Pease, A., Schmidt, M., Guhe, M. & Kuehnberger, K-U. (2017). Theory blending: extended algorithmic aspects and examples. Annals of Mathematics and Artificial Intelligence, 80(1), pp. 65-89. doi: 10.1007/s10472-016-9505-y
Harder, F. & Besold, T. R. (2017). An approach to supervised learning of three valued Lukasiewicz logic in Hölldobler's core method. CEUR Workshop Proceedings, 1895, pp. 24-37.
Besold, T. R., Hedblom, M. M. & Kutz, O. (2017). A narrative in three acts: Using combinations of image schemas to model events. Biologically Inspired Cognitive Architectures, 19, pp. 10-20. doi: 10.1016/j.bica.2016.11.001
Schmid, U., Zeller, C., Besold, T. R. , Tamaddoni-Nezhad, A. & Muggleton, S. (2017). How does predicate invention affect human comprehensibility?. Lecture Notes in Computer Science, 10326 , pp. 52-67. doi: 10.1007/978-3-319-63342-8_5
Besold, T. R., Garcez, A.D, Stenning, K. , van der Torre, L. & van Lambalgen, M. (2017). Reasoning in non-probabilistic uncertainty: logic programming and neural-symbolic computing as examples. Minds and Machines, 27(1), pp. 37-77. doi: 10.1007/s11023-017-9428-3
Besold, T. R., Kuhnberger, K-U. & Plaza, E. (2017). Towards a computational- and algorithmic-level account of concept blending using analogies and amalgams. Connection Science, 29(4), pp. 387-413. doi: 10.1080/09540091.2017.1326463
Besold, T. R., Kuehnberger, K-U., Garcez, A. , Saffiotti, A., Fischer, M. H. & Bundy, A. (2015). Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition. Lecture Notes in Computer Science, 9205, pp. 35-45. doi: 10.1007/978-3-319-21365-1_4
Besold, T. R. & Kuhnberger, K-U. (2015). Towards integrated neural-symbolic systems for human-level AI: Two research programs helping to bridge the gaps. Biologically Inspired Cognitive Architectures, 14, pp. 97-110. doi: 10.1016/j.bica.2015.09.003
Besold, T. R., Hernández-Orallo, J. & Schmid, U. (2015). Can Machine Intelligence be Measured in the Same Way as Human intelligence?. Kunstliche Intelligenz, 29(3), pp. 291-297. doi: 10.1007/s13218-015-0361-4
Martinez, M., Krumnack, U., Smaill, A. , Besold, T. R., Abdel-Fattah, A. M. H., Schmidt, M., Gust, H., Kuhnberger, K-U., Guhe, M. & Pease, A. (2014). Algorithmic aspects of theory blending. Lecture Notes in Computer Science, 8884, pp. 180-192. doi: 10.1007/978-3-319-13770-4_16
Besold, T. R. & Kuhnberger, K-U. (2014). Applying AI for modeling and understanding analogy-based classroom teaching tools and techniques. Lecture Notes in Computer Science, 8736, pp. 55-61. doi: 10.1007/978-3-319-11206-0_6
Besold, T. R. (2014). A note on chances and limitations of psychometric AI. Lecture Notes in Computer Science, 8736, pp. 49-54. doi: 10.1007/978-3-319-11206-0_5
Besold, T. R. (2013). Rationality in context: An analogical perspective. Lecture Notes in Computer Science, 8175 L, pp. 129-142. doi: 10.1007/978-3-642-40972-1_10
Besold, T. R. (2013). Human-level artificial intelligence must be a science. Lecture Notes in Computer Science, 7999 L, pp. 174-177. doi: 10.1007/978-3-642-39521-5_19
Besold, T. R. & Robere, R. (2013). When almost is not even close: Remarks on the approximability of HDTP. Lecture Notes in Computer Science, 7999 L, pp. 11-20. doi: 10.1007/978-3-642-39521-5_2
Besold, T. R. & Robere, R. (2013). A note on tractability and artificial intelligence. Lecture Notes in Computer Science, 7999 L, pp. 170-173. doi: 10.1007/978-3-642-39521-5_18
Book
Besold, T. R., ed. (2018). Pre-Proceedings of the Cognitive Computation Symposium: Thinking Beyond Deep Learning (CoCoSym 2018) : Extended Abstracts/Speakers' Positions. London: City, University of London.
Conference or Workshop Item
Confalonieri, R., Weyde, T. ORCID: 0000-0001-8028-9905, Besold, T. R. & Moscoso del Prado Martín, F. (2020).
Trepan Reloaded: A Knowledge-driven Approach to Explaining Artificial Neural Networks.
In:
24th European Conference on Artificial Intelligence (ECAI 2020).
24th European Conference on Artificial Intelligence (ECAI 2020), 29 Aug - 08 Sep 2020, Santiago de Compostela, Spain.
doi: 10.3233/FAIA200378
Garcez, A., Besold, T. R., Raedt, L. , Foldiak, P., Hitzler, P., Icard, T., Kuhnberger, K-U., Lamb, L. C., Miikkulainen, R. & Silver, D. L. (2015). Neural-Symbolic Learning and Reasoning: Contributions and Challenges. Paper presented at the 2015 AAAI Spring Symposium Series, 23-03-2015 - 25-03-2015, Stanford University, USA.