A Brief Survey of Associations Between Meta-Learning and General AI
Artificial Intelligence
2021-01-13 v1 Machine Learning
Abstract
This paper briefly reviews the history of meta-learning and describes its contribution to general AI. Meta-learning improves model generalization capacity and devises general algorithms applicable to both in-distribution and out-of-distribution tasks potentially. General AI replaces task-specific models with general algorithmic systems introducing higher level of automation in solving diverse tasks using AI. We summarize main contributions of meta-learning to the developments in general AI, including memory module, meta-learner, coevolution, curiosity, forgetting and AI-generating algorithm. We present connections between meta-learning and general AI and discuss how meta-learning can be used to formulate general AI algorithms.
Keywords
Cite
@article{arxiv.2101.04283,
title = {A Brief Survey of Associations Between Meta-Learning and General AI},
author = {Huimin Peng},
journal= {arXiv preprint arXiv:2101.04283},
year = {2021}
}