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Fusing Trajectories of Exploring Agents in a Crisis Environment using DeepSeek

Conference Paper (2025)
Author(s)

Leon Rothkrantz (TU Delft - Interactive Intelligence)

Siska Fitrianie (TU Delft - Interactive Intelligence)

DOI related publication
https://doi.org/10.1109/InfoTech67177.2025.11175940 Final published version
More Info
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Publication Year
2025
Language
English
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. 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.
Publisher
IEEE
ISBN (electronic)
9798331597627
Event
Downloads counter
54
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

During a natural disaster, when roads are damaged or blocked, rescue agents search the area to find new routes from start to destination. Their trajectories are sent to a crisis center and merged into a new map. The DeepSeek and ChatGPT algorithms help build this map by combining the agents' explored routes. This paper presents the algorithm and its application.

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