Items where City Author is "Besold, Tarek-r"

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Number of items: 22.


Muggleton, S., Schmid, U., Zeller, C., Tamaddoni-Nezhad, A. & Besold, T. R. (2018). Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP. Machine Learning, 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, doi: 10.1080/0952813X.2018.1430860

Harder, F. & Besold, T. R. (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.

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

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), doi: 10.1007/s11023-017-9428-3

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:

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, 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, 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, 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, pp. 170-173. doi: 10.1007/978-3-642-39521-5_18


T. R. Besold, ed. (2018). Pre-Proceedings of the Cognitive Computation Symposium: Thinking Beyond Deep Learning (CoCoSym 2018) : Extended Abstracts/Speakers' Positions. London: City, University of London.

This list was generated on Mon Jul 16 04:31:25 2018 UTC.