# Random Walk in Random Permutation Set Theory

arXiv: https://arxiv.org/abs/2404.03978 · HTML: https://mlsanity.com/paper/2404.03978/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 53 references that are in the map.
- First posted on arXiv 5 Apr 2024.

## Builds on (most cited first, 4 of 4)

- [Maximum Entropy of Random Permutation Set](https://mlsanity.com/paper/2203.11941/) (2021)
- [Limit of the Maximum Random Permutation Set Entropy](https://mlsanity.com/paper/2403.06206/) (2024)
- [Random Graph Set and Evidence Pattern Reasoning Model](https://mlsanity.com/paper/2402.13058/) (2024)
- [Learnable WSN Deployment of Evidential Collaborative Sensing Model](https://mlsanity.com/paper/2403.15728/) (2024)

## Built on by (most cited first, 1 of 1)

- [Evaluating Evidential Reliability In Pattern Recognition Based On Intuitionistic Fuzzy Sets](https://mlsanity.com/paper/2411.00848/) (2024)

## Abstract (arXiv)

Random walk is an explainable approach for modeling natural processes at the molecular level. The Random Permutation Set Theory (RPST) serves as a framework for uncertainty reasoning, extending the applicability of Dempster-Shafer Theory. Recent explorations indicate a promising link between RPST and random walk. In this study, we conduct an analysis and construct a random walk model based on the properties of RPST, with Monte Carlo simulations of such random walk. Our findings reveal that the random walk generated through RPST exhibits characteristics similar to those of a Gaussian random walk and can be transformed into a Wiener process through a specific limiting scaling procedure. This investigation establishes a novel connection between RPST and random walk theory, thereby not only expanding the applicability of RPST, but also demonstrating the potential for combining the strengths of both approaches to improve problem-solving abilities.