335 citations · 593 across the 4 of their papers we have counts for
6 papers
The Next Big Thing(s) in Unsupervised Machine Learning: Five Lessons from Infant Learning
Lorijn Zaadnoordijk, Tarek R. Besold, Rhodri Cusack
After a surge in popularity of supervised Deep Learning, the desire to reduce the dependence on curated, labelled data sets and to leverage the vast quantities of unlabelled data a…
Trepan Reloaded: A Knowledge-driven Approach to Explaining Artificial Neural Networks
Roberto Confalonieri, Tillman Weyde, Tarek R. Besold +1
Explainability in Artificial Intelligence has been revived as a topic of active research by the need of conveying safety and trust to users in the `how' and `why' of automated deci…
The What, the Why, and the How of Artificial Explanations in Automated Decision-Making
Tarek R. Besold, Sara L. Uckelman
The increasing incorporation of Artificial Intelligence in the form of automated systems into decision-making procedures highlights not only the importance of decision theory for a…
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
Tarek R. Besold, Artur d'Avila Garcez, Sebastian Bader +11
The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several…
What Does Explainable AI Really Mean? A New Conceptualization of Perspectives
Derek Doran, Sarah Schulz, Tarek R. Besold
We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where…
Reasoning in Non-Probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples
Tarek R. Besold, Artur d'Avila Garcez, Keith Stenning +2
This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for p…