Towards learning-to-learn

Publication date: October 2019Source: Current Opinion in Behavioral Sciences, Volume 29Author(s): Benjamin James Lansdell, Konrad Paul KordingIn good old-fashioned artificial intelligence (GOFAI), humans specified systems that solved problems. Much of the recent progress in AI has come from replacing human insights by learning. These learning systems are usually built by humans. Yet there is no reason to believe that humans are particularly good at defining such systems: we may expect learning to be better if we learn it. Recent research in machine learning has started to realize the benefits of that strategy. We should thus expect this to be relevant for neuroscience: how could the correct learning rules be acquired? Cognitive science has long shown that humans learn-to-learn. Here we discuss ideas across machine learning, neuroscience, and cognitive science that matter for the principle of learning-to-learn.
Source: Current Opinion in Behavioral Sciences - Category: Psychiatry & Psychology Source Type: research