Kumaran et al. (2016)

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated

Trends in Cognitive Sciences, 20(7), 512-534

Find It

DOI

Abstract

Updates complementary learning systems theory. Broadens the role of hippocampal replay to include goal-dependent reweighting of experience statistics, addresses two empirical challenges by showing that recurrent activation of hippocampal traces can support some generalisation and that neocortical learning can be rapid for information consistent with existing structure, and draws links between the theory and machine learning architectures that pair a network with an external memory module.

Reference

Kumaran, D., Hassabis, D., & McClelland, J. L. (2016). What learning systems do intelligent agents need? Complementary learning systems theory updated. Trends in Cognitive Sciences, 20(7), 512–534. https://doi.org/10.1016/j.tics.2016.05.004

What Rests on This

Cited in the argument rather than behind a score: this is one of the papers the taxonomy is built on, named where the site explains itself rather than in the findings under a mechanism.