Summary of Lgr2: Language Guided Reward Relabeling For Accelerating Hierarchical Reinforcement Learning, by Utsav Singh et al.
LGR2: Language Guided Reward Relabeling for Accelerating Hierarchical Reinforcement Learning
by Utsav Singh, Pramit Bhattacharyya, Vinay P. Namboodiri
First submitted to arxiv on: 9 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation and Language (cs.CL); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel Hierarchical Reinforcement Learning (HRL) framework called LGR2, which tackles the challenge of translating natural language instructions into low-level robotic actions. The framework mitigates non-stationarity in HRL by using language-guided higher-level rewards that remain unaffected by the changing lower-level policy behavior. Experimental results show that LGR2 effectively achieves success rates exceeding 70% in challenging robotic navigation and manipulation environments, outperforming baselines. The paper’s contributions include a novel approach to solving complex robotic control tasks with natural language instructions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers developed a new way for robots to understand and follow human instructions. They used a special type of machine learning called Hierarchical Reinforcement Learning (HRL) that helps robots learn from their mistakes. The team created a new framework, LGR2, which makes it easier for robots to understand what they need to do by giving them clear goals at the top level and letting them figure out how to get there step-by-step. This approach helped robots complete complex tasks like navigating and manipulating objects, even when it was difficult or rewarded only occasionally. In real-world experiments, LGR2 performed better than other methods. |
Keywords
» Artificial intelligence » Machine learning » Reinforcement learning
