Reinforcement learning: bringing together computation and cognition
Abstract
A key aspect of human intelligence is our ability to learn very quickly. This ability is still lacking in artificial intelligence. This article will highlight recent research showing how bringing together the fields of artificial intelligence and cognitive science may benefit both. Ideas from artificial intelligence have provided helpful formal theories to account for aspects of human learning. In return, ideas from cognitive science and neuroscience can also inform artificial intelligence research with directions to make algorithms more human-like. For example, recent work shows that human learning can only be understood in the context of multiple separate, interacting memory systems, rather than as a single, complex learner. This insight is starting to show promise in improving artificial agents’ learning efficiency.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.