A Brief Survey of Associations Between Meta-Learning and General AI

2021/01/12 by Huimin Peng, Peng, Huimin
Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification

paper · pdf · doi:10.48550/arxiv.2101.04283

openalex publication_date 2021/01/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Coevolution of hosts and parasites
• Least angle regression
• Long Short-Term Memory
• Deep Learning in Neural Networks: An Overview
• Parasite—host coevolution
• On Learning to Think: Algorithmic Information Theory for Novel\n Combinations of Reinforcement Learning Controllers and Recurrent Neural World\n Models
• The unreasonable effectiveness of the forget gate
• AI-GAs: AI-generating algorithms, an alternate paradigm for producing\n general artificial intelligence
• A Comprehensive Overview and Survey of Recent Advances in Meta-Learning

Related

• A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
• A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning
• Meta-Learning in Neural Networks: A Survey
• Advances and Challenges in Meta-Learning: A Technical Review
• A Metamodel and Framework for Artificial General Intelligence From\n Theory to Practice