Summary of Grounding From An Ai and Cognitive Science Lens, by Goonmeet Bajaj et al.
Grounding from an AI and Cognitive Science Lens
by Goonmeet Bajaj, Srinivasan Parthasarathy, Valerie L. Shalin, Amit Sheth
First submitted to arxiv on: 19 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 tackle the complex problem of grounding from multiple perspectives, combining insights from cognitive science and machine learning. They delve into the subtleties of grounding, highlighting its importance for collaborative agents and exploring similarities and differences between approaches in both fields. The authors also investigate the potential of neuro-symbolic methods tailored for grounding tasks, demonstrating how these can better address this challenge. Finally, they identify areas ripe for further exploration and development. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Grounding is a tricky problem that helps robots and computers understand what words mean. This paper looks at grounding from two angles: how our brains work and how machines learn. It shows how grounding is important when robots or computers need to work together. The paper also talks about new ways of combining brain-like thinking with computer programs to make grounding easier. Overall, this research helps us better understand how we can make robots and computers more helpful. |
Keywords
» Artificial intelligence » Grounding » Machine learning
