Suggested further readings#

Overview#

Sutton, R. S., and Barto, A. G. (2018). Reinforcement learning: An introduction. MIT press.

State of the art#

Dabney, W., Kurth-Nelson, Z., Uchida, N., Starkweather, C. K., Hassabis, D., Munos, R., and Botvinick, M. (2020). A distributional code for value in dopamine-based reinforcement learning. Nature 577(7792): 671-675. doi: 10.1038/s41586-019-1924-6 Closed Access publication (postprint: europepmc.org/articles/pmc7476215 Open Access publication).

Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., … and Hassabis, D. (2015). Human-level control through deep reinforcement learning. Nature 518(7540): 529-533. doi: 10.1038/nature14236 Closed Access publication.

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., … and Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature 529(7587): 484-489. doi: 10.1038/nature16961 Closed Access publication.