Research map / Reinforcement learning / Visual and representation RL
DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Data-Efficient Hierarchical Reinforcement Learning (NeurIPS 2018 · similarity 0.91)
- Hierarchical Reinforcement Learning with Targeted Causal Interventions (ICML 2025 · similarity 0.90)
- Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning (NeurIPS 2023 · similarity 0.90)
- Reconciling Spatial and Temporal Abstractions for Goal Representation (ICLR 2024 · similarity 0.89)
- Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning (ICML 2025 · similarity 0.89)
- Flattening Hierarchies with Policy Bootstrapping (NeurIPS 2025 · similarity 0.88)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
