Deep Reinforcement Learning in Action

Reference list

We did our best to cite the projects and papers we used in the individual chapters, but a lot of the approaches and ideas we used were inspired by the sources listed here, even if they were not directly used. For example, we used a lot of string diagrams, which were not taken from any one source but were inspired by several of the papers listed here, including one about quantum mechanics (Coecke and Kissinger, 2017). While we include this bibliography primarily to give credit where credit is due, you may find these references useful as you delve deeper into deep reinforcement learning and adjacent fields.

• Andrew, A.M. 1998. “Reinforcement learning: An introduction.” Kybernetes 27. https://doi.org/10.1108/k.1998.27.9.1093.3.