Summary of The Negation Of Permutation Mass Function, by Yongchuan Tang et al.
The negation of permutation mass function
by Yongchuan Tang, Rongfei Li
First submitted to arxiv on: 11 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Information Theory (cs.IT)
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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 approach to applying negation in random permutation sets theory, building upon existing methods from probability theory, evidence theory, and complex evidence theory. The authors introduce the concept of negation of permutation mass function, verify its convergence, and explore the trends of uncertainty and dissimilarity after each operation. Numerical examples demonstrate the effectiveness of the proposed method. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper shows how to use a new way of thinking about information, called random permutation sets theory, to understand things better. It’s like taking a puzzle apart and putting it back together in a different way. The authors came up with a new idea for making this kind of thinking work better by using something called “negation”. They tested their idea and showed that it makes sense. |
Keywords
» Artificial intelligence » Probability
