1 citations · 1 across the 3 of their papers we have counts for
3 papers
Teaching and Learning under Deductive Errors
Jan Arne Telle, Brigt Håvardstun, Jose Hernandez-Orallo
Most models of machine teaching and learning assume the learner makes no errors in its internal deductive inference. However, humans and large language models in few-shot learning…
When Redundancy Matters: Machine Teaching of Representations
Cèsar Ferri, Dario Garigliotti, Brigt Arve Toppe Håvardstun +2
In traditional machine teaching, a teacher wants to teach a concept to a learner, by means of a finite set of examples, the witness set. But concepts can have many equivalent repre…
The Animal-AI Environment: A Virtual Laboratory For Comparative Cognition and Artificial Intelligence Research
Konstantinos Voudouris, Ibrahim Alhas, Wout Schellaert +11
The Animal-AI Environment is a unique game-based research platform designed to facilitate collaboration between the artificial intelligence and comparative cognition research commu…