A First Empirical Study of Emphatic Temporal Difference Learning. - Sina Ghiassian; Banafsheh Rafiee; Richard S. Sutton (CoRR, 2017)

Two geometric input transformation methods for fast online reinforcement learning with neural nets. - Sina Ghiassian; Huizhen Yu; Banafsheh Rafiee; Richard S. Sutton (CoRR, 2018)

Prediction in Intelligence: An Empirical Comparison of Off-policy Algorithms on Robots. - Banafsheh Rafiee; Sina Ghiassian; Adam White 001; Richard S. Sutton (AAMAS, 2019)

Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. - Sina Ghiassian; Banafsheh Rafiee; Yat Long Lo; Adam White 001 (AAMAS, 2020)

Testbeds for Reinforcement Learning. - Banafsheh Rafiee (CoRR, 2020)

What makes useful auxiliary tasks in reinforcement learning: investigating the effect of the target policy. - Banafsheh Rafiee; Jun Jin 001; Jun Luo 009; Adam White 001 (CoRR, 2022)

Auxiliary task discovery through generate-and-test. - Banafsheh Rafiee; Sina Ghiassian; Jun Jin 001; Richard S. Sutton; Jun Luo 009; Adam White 001 (CoLLAs, 2023)

From eye-blinks to state construction: Diagnostic benchmarks for online representation learning. - Banafsheh Rafiee; Zaheer Abbas; Sina Ghiassian; Raksha Kumaraswamy; Richard S. Sutton; Elliot A. Ludvig; Adam White 001 (Adapt. Behav., 2023)

Off-Policy Prediction Learning: An Empirical Study of Online Algorithms. - Sina Ghiassian; Banafsheh Rafiee; Richard S. Sutton (IEEE Trans. Neural Networks Learn. Syst., 2025)

Concise Reasoning via Reinforcement Learning. - Mehdi Fatemi; Banafsheh Rafiee; Mingjie Tang; Kartik Talamadupula (CoRR, 2025)