awesome-gcrl

Research Papers

ICML 2024

1. Zheng S, Bai C, Yang Z, et al. How Does Goal Relabeling Improve Sample Efficiency?[C]//Forty-first International Conference on Machine Learning. 2024. [Paper]

2. Wang V H, Wang T, Yang W, et al. Probabilistic subgoal representations for hierarchical reinforcement learning[C]//Forty-first International Conference on Machine Learning. 2024. [Paper]

3. Jain V, Ravanbakhsh S. Learning to Reach Goals via Diffusion[C]//Forty-first International Conference on Machine Learning. 2024. [Paper]

4. Na H, Moon I. LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning[C]//Forty-first International Conference on Machine Learning. 2024. [Paper]

NeurIPS 2024

1. Gong X, Feng D, Xu K, et al. Goal-Conditioned On-Policy Reinforcement Learning[C]//The Thirty-eighth Annual Conference on Neural Information Processing Systems. 2024. [Paper] [Code]

2. Duan Y, Cui G, Zhu H. Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning[C]//The Thirty-eighth Annual Conference on Neural Information Processing Systems. 2024. [Paper]

3. Cheng H, Brown J W. Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning[C]//The Thirty-eighth Annual Conference on Neural Information Processing Systems. 2024. [Paper]

4. Yalcinkaya B, Lauffer N, Vazquez-Chanlatte M, et al. Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning[C]//The Thirty-eighth Annual Conference on Neural Information Processing Systems. 2024. [Paper]

5. Wu J, Wang Y, Li L, et al. Goal Conditioned Reinforcement Learning for Photo Finishing Tuning[C]//The Thirty-eighth Annual Conference on Neural Information Processing Systems. 2024. [Paper]

ICLR 2025

TBD

GCRL environments

1. Gong X, Feng D, Xu K, et al. VVC-Gym: A Fixed-Wing UAV Reinforcement Learning Environment for Multi-Goal Long-Horizon Problems[C]//International Conference on Learning Representations. ICLR, 2025. [Paper] [Code]

2. Gymnasium-Robotics. [Code]

3. Gallouédec Q, Cazin N, Dellandréa E, et al. panda-gym: Open-source goal-conditioned environments for robotic learning[C]//4th Robot Learning Workshop: Self-Supervised and Lifelong Learning@ NeurIPS 2021. 2021. [Paper] [Code]

4. Park S, Frans K, Eysenbach B, et al. Ogbench: Benchmarking offline goal-conditioned rl[C]//International Conference on Learning Representations. ICLR, 2025. [Paper] [Code]

5. Plappert M, Andrychowicz M, Ray A, et al. Multi-goal reinforcement learning: Challenging robotics environments and request for research[J]. arxiv preprint arxiv:1802.09464, 2018. [Paper]