Deep Reinforcement Learning Methods for Navigational Aids. - Bijan Fakhri; Aaron Keech; Joel Schlosser; Ethan Brooks; Hemanth Venkateswara; Sethuraman Panchanathan; Zsolt Kira (ICSM, 2018)

Reinforcement Learning of Implicit and Explicit Control Flow Instructions. - Ethan Brooks; Janarthanan Rajendran; Richard L. Lewis; Satinder Singh 001 (ICML, 2021)

In-Context Policy Iteration. - Ethan Brooks; Logan Walls; Richard L. Lewis; Satinder Singh 001 (CoRR, 2022)

In-context Reinforcement Learning with Algorithm Distillation. - Michael Laskin; Luyu Wang; Junhyuk Oh; Emilio Parisotto; Stephen Spencer; Richie Steigerwald; DJ Strouse; Steven Stenberg Hansen; Angelos Filos; Ethan Brooks; Maxime Gazeau; Himanshu Sahni; et al. (ICLR, 2023)

Large Language Models can Implement Policy Iteration. - Ethan Brooks; Logan Walls; Richard L. Lewis; Satinder Singh 001 (NeurIPS, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

Explorations of In-Context Reinforcement Learning - Ethan Brooks (2024)