Towards Solving Text-based Games by Producing Adaptive Action Spaces. - Ruo Yu Tao; Marc-Alexandre Côté; Xingdi Yuan; Layla El Asri (CoRR, 2018)

Novelty Search in Representational Space for Sample Efficient Exploration. - Ruo Yu Tao; Vincent François-Lavet; Joelle Pineau (NeurIPS, 2020)

Measuring and Mitigating Interference in Reinforcement Learning. - Vincent Liu; Han Wang; Ruo Yu Tao; Khurram Javed; Adam White 001; Martha White (CoLLAs, 2023)

Agent-State Construction with Auxiliary Inputs. - Ruo Yu Tao; Adam White 001; Marlos C. Machado (Trans. Mach. Learn. Res., 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)

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)