Add Deletang paper

lichess.bib

@@ -172,6 +172,13 @@ @article{de-marzo:2023:complexity-similarity-chess-openings-community-data
   abstract      = {Chess is a centuries-old game that continues to be widely played worldwide. Opening Theory is one of the pillars of chess and requires years of study to be mastered. In this paper, we use the games played in an online chess platform to exploit the ``wisdom of the crowd'' and answer questions traditionally tackled only by chess experts. We first define a relatedness network of chess openings that quantifies how similar two openings are to play. Using this network, we identify communities of nodes corresponding to the most common opening choices and their mutual relationships. Furthermore, we demonstrate how the relatedness network can be used to forecast future openings players will start to play, with back-tested predictions outperforming a random predictor. We then apply the Economic Fitness and Complexity algorithm to measure the difficulty of openings and players' skill levels. Our study not only provides a new perspective on chess analysis but also opens the possibility of suggesting personalized opening recommendations using complex network theory.},
 }
 
+@misc{deletang:2024:generative-reinforcement-learning-with-transformers,
+  title         = {Generative Reinforcement Learning with Transformers},
+  author        = {Gregoire Deletang and Anian Ruoss and Li Kevin Wenliang and Elliot Catt and Tim Genewein and Jordi Grau-Moya and Marcus Hutter and Joel Veness},
+  year          = {2024},
+  url           = {https://openreview.net/forum?id=6qtDu7hVPF},
+}
+
 @inproceedings{demeter:2021:probing-learning-representation-language-models-closed-domains,
   title         = {Who{'}s on First?: Probing the Learning and Representation Capabilities of Language Models on Deterministic Closed Domains},
   author        = {Demeter, David  and Downey, Doug},

lichess.html

@@ -309,6 +309,15 @@
 href="https://doi.org/10.1038/s41598-023-31658-w">10.1038/s41598-023-31658-w</a>.
 </div>
 <div
+id="ref-deletang:2024:generative-reinforcement-learning-with-transformers"
+class="csl-entry" role="listitem">
+Deletang, Gregoire, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Tim
+Genewein, Jordi Grau-Moya, Marcus Hutter, and Joel Veness.
+<span>“Generative Reinforcement Learning with Transformers,”</span>
+2024. <a
+href="https://openreview.net/forum?id=6qtDu7hVPF">https://openreview.net/forum?id=6qtDu7hVPF</a>.
+</div>
+<div
 id="ref-demeter:2021:probing-learning-representation-language-models-closed-domains"
 class="csl-entry" role="listitem">
 Demeter, David, and Doug Downey. <span>“Who<span>’</span>s on First?: