Research map / Reinforcement learning / Policy gradient and actor-critic
Learning to Repeat: Fine Grained Action Repetition for Deep 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
- Select before Act: Spatially Decoupled Action Repetition for Continuous Control (ICLR 2025 · similarity 0.88)
- Learning Uncertainty-Aware Temporally-Extended Actions (AAAI 2024 · similarity 0.85)
- Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration (ICLR 2025 · similarity 0.85)
- No Prior Mask: Eliminate Redundant Action for Deep Reinforcement Learning (AAAI 2024 · similarity 0.85)
- Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL (NeurIPS 2024 · similarity 0.85)
- Improving planning and MBRL with temporally-extended actions (NeurIPS 2025 · similarity 0.85)
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.