My name is Jordi Bieger and I'm currently pursuing a PhD at Reykjavik University under the guidance of Dr. Kristinn R. Thórisson. My overarching research topic is Artificial Pedagogy: the study of teaching / training / raising / educating AI systems, with a particular eye towards Artificial General Intelligence. I want to develop a theory for how different teaching techniques such as demonstration, heuristic rewarding, simplification and decomposition can help AI systems learn. How can we shape the environment and present training data? How can we interactively determine learning progress and remedy deficiencies?
To answer these questions we need a Task Theory for modeling tasks, and AI Evaluation for (interactively) determining the (hopefully growing) capabilities of learning systems. Related research interests include: Transfer Learning, Lifelong Learning, Multitask Learning, Multiagent Learning, Semi-supervised Learning, Active Learning, Computational Learning Theory, and Reinforcement Learning.
I'm currently helping organize the Workshop on Architectures and Evaluation for Generality, Autonomy and Progress in AI (AEGAP 2018) at the Federated AI Meeting (IJCAI, ECAI, ICML, AAMAS, etc.) on July 13/14/15 (TBD) in Stockholm, Sweden. Please submit a paper if you're interested!
|Name:||Jordi Erwan Bieger|
|Date of birth:||December 9, 1985|
|Place of birth:||Voorburg, The Netherlands|
|Phone:||+354 666 7701|