A Framework for Long-Term Learning Systems

A Framework for Long-Term Learning Systems

Diana Benavides-Prado

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Doctoral Consortium. Pages 5167-5168. https://doi.org/10.24963/ijcai.2017/743

Increasing amounts of data have made the use of machine learning techniques much more widespread. A lot of research in machine learning has been dedicated to the design and application of effective and efficient algorithms to explain or predict facts. The development of intelligent machines that can learn over extended periods of time, and that improve their abilities as they execute more tasks, is still a pending contribution from computer science to the world. This weakness has been recognised for some decades, and an interest to solve it seems to be increasing, as demonstrated by recent leading work and broader discussions at main events in the field [Chen and Liu, 2015; Chen et al., 2016]. Our research is intended to help fill that gap.
Keywords:
Artificial Intelligence: computer science
Artificial Intelligence: machine learning