Mean Actor Critic. - Kavosh Asadi; Cameron Allen; Melrose Roderick; Abdel-rahman Mohamed; George Dimitri Konidaris; Michael L. Littman (CoRR, 2017)

Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic. - Cameron Allen; Tim Klinger; George Konidaris 001; Matthew Riemer; Gerald Tesauro (CoRR, 2020)

Efficient Black-Box Planning Using Macro-Actions with Focused Effects. - Cameron Allen; Michael Katz 001; Tim Klinger; George Konidaris 001; Matthew Riemer; Gerald Tesauro (IJCAI, 2021)

Learning Markov State Abstractions for Deep Reinforcement Learning. - Cameron Allen; Neev Parikh; Omer Gottesman; George Konidaris 001 (NeurIPS, 2021)

Bad-Policy Density: A Measure of Reinforcement Learning Hardness. - David Abel; Cameron Allen; Dilip Arumugam; D. Ellis Hershkowitz; Michael L. Littman; Lawson L. S. Wong (CoRR, 2021)

Coarse-Grained Smoothness for RL in Metric Spaces. - Omer Gottesman; Kavosh Asadi; Cameron Allen; Sam Lobel; George Konidaris 001; Michael Littman 002 (CoRR, 2021)

Optimistic Initialization for Exploration in Continuous Control. - Sam Lobel; Omer Gottesman; Cameron Allen; Akhil Bagaria; George Konidaris 001 (AAAI, 2022)

Characterizing the Action-Generalization Gap in Deep Q-Learning. - Zhiyuan Zhou; Cameron Allen; Kavosh Asadi; George Konidaris 001 (CoRR, 2022)

Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces. - Omer Gottesman; Kavosh Asadi; Cameron S. Allen; Samuel Lobel; George Konidaris 001; Michael Littman 002 (AISTATS, 2023)

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy. - Cameron Allen; Aaron Kirtland; Ruo Yu Tao; Sam Lobel; Daniel Scott; Nicholas Petrocelli; Omer Gottesman; Ronald Parr; Michael L. Littman; George Konidaris 001 (NeurIPS, 2024)

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. - Erik Jenner; Shreyas Kapur; Vasil Georgiev; Cameron Allen; Scott Emmons; Stuart J. Russell (NeurIPS, 2024)

Benchmarking Partial Observability in Reinforcement Learning with a Suite of Memory-Improvable Domains. - Ruo Yu Tao; Kaicheng Guo; Cameron Allen; George Dimitri Konidaris (CoRR, 2025)