Encounter-Based Density Approximation Using Multi-step and Quantum-Inspired Random Walks

Robert S. Wezeman, Niel M.P. Neumann, Frank Phillipson, Robert E. Kooij*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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In this paper we study encounter-based density estimation using different random walks and analyse the effects of the step-size on the convergence of the density approximation. Furthermore, we analyse different types of random walks, namely, a uniform random walk, with every position equally likely to be visited next, a classical random walk and a quantum-inspired random walk, where the probability distribution for the next state is sampled from a quantum random walk. We find that walks with additional steps lead to faster convergence, but that the type of step, quantum-inspired or classical, has only a marginal effect.

Original languageEnglish
Title of host publicationIntelligent Computing - Proceedings of the 2023 Computing Conference
EditorsKohei Arai
Place of PublicationCham
Number of pages15
ISBN (Electronic)978-3-031-37717-4
ISBN (Print)978-3-031-37716-7
Publication statusPublished - 2023
EventProceedings of the Computing Conference 2023 - London, United Kingdom
Duration: 22 Jun 202323 Jun 2023

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceProceedings of the Computing Conference 2023
Country/TerritoryUnited Kingdom

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


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