Research map / Reinforcement learning / Visual and representation RL
Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
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
- Autonomous Option Invention for Continual Hierarchical Reinforcement Learning and Planning (AAAI 2025 · similarity 0.90)
- Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control (ICLR 2025 · similarity 0.90)
- RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning (ICML 2024 · similarity 0.90)
- Action abstractions for amortized sampling (ICLR 2025 · similarity 0.89)
- Learning Agentic Policy from Action Guidance (NeurIPS 2026 · similarity 0.89)
- Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking (NeurIPS 2024 · similarity 0.89)
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.
