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Meta-learning is one of the most active research fields in the field of deep learning. Some schools of artificial intelligence agree with the view that meta-learning is a stepping stone to unlock artificial general intelligence (AGI).
In recent years, the research and development of meta-learning technology has exploded. The idea behind meta-learning can be traced back to 1979. Donald B. Maudsley redefines the new cognitive paradigm in his works as “learners realize and gradually control their internalized perception, inquiry , Learning and growing habits”.
Meta-learning
In 1985, John Biggs defined meta-learning more simply as “understanding and controlling self-learning” in his work. Although these definitions are accurate from the perspective of cognitive science, it seems difficult to adapt to the specific work of artificial intelligence.
In artificial intelligence systems, meta-learning can be simply defined as the ability to acquire the versatility of knowledge. Humans can acquire multiple tasks at the same time with minimal information. We can recognize a new object by looking at a single picture, or we can learn complex multitasking activities at the same time, such as driving a car or flying an airplane.
