Summary of Shared Control with Black Box Agents Using Oracle Queries, by Inbal Avraham et al.
Shared Control with Black Box Agents using Oracle Queries
by Inbal Avraham, Reuth Mirsky
First submitted to arxiv on: 25 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: 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 In this paper, researchers explore shared control problems where robots collaborate with humans to achieve a common goal. They investigate how direct communication between agents can enhance learning efficiency and accuracy by extending the traditional shared control framework to include querying capabilities. The authors propose three heuristics for deciding when to query: reinforcement learning-based, utility-based, and entropy-based, aiming to minimize overall learning costs. Experimental results on two environments demonstrate the benefits of querying in achieving better control policies while highlighting tradeoffs between different heuristics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about robots working with humans to get things done. It’s like a team effort! The scientists found that if the robot can ask questions to its human partner, it can learn faster and make better decisions. They came up with three ways for the robot to decide when to ask: one way uses past experiences, another looks at what’s most important, and the third considers how much the robot knows already. By asking questions, the robot can figure out a better way to control things and make life easier. |
Keywords
» Artificial intelligence » Reinforcement learning
