Summary of Human-aware Belief Revision: a Cognitively Inspired Framework For Explanation-guided Revision Of Human Models, by Stylianos Loukas Vasileiou et al.
Human-Aware Belief Revision: A Cognitively Inspired Framework for Explanation-Guided Revision of Human Models
by Stylianos Loukas Vasileiou, William Yeoh
First submitted to arxiv on: 29 May 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 The proposed Human-Aware Belief Revision framework is a cognitively-inspired approach that models human belief revision dynamics, departing from traditional frameworks which rely on minimal changes to existing beliefs. The new method considers people’s inherent drive to seek explanations for inconsistencies and strive for explanatory understanding. This framework is evaluated through two human-subject studies under real-world scenarios, supporting the hypotheses and providing insights into how people resolve inconsistencies. The results offer guidance for developing more effective AI systems that are aware of human cognition. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The Human-Aware Belief Revision framework is a new way to understand how humans change their beliefs when they find something inconsistent. Traditional ways of changing beliefs focus on making the smallest changes possible, but this doesn’t match how people really think. People want to know why things don’t make sense and try to fix it with an explanation. The framework is designed to mimic human thinking and tests it in real-life scenarios with people as participants. The results show that humans use different strategies to resolve inconsistencies and can help create more intelligent AI systems. |
