Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations. Lin, F. & Knoblock, C. A. In Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, of SIGSPATIAL '23, New York, NY, USA, 2023. Association for Computing Machinery. ![Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Private vehicles are a direct means to bring people from one place to their desired destinations. However, no omniscient dispatcher is handling the origin-destination of vehicles and the availability of stationary resources, such as parking spaces or charging stations. Competitive cruising for stationary resources leads to environmental pollution and is a waste of drivers' time. We focus on the problem of distributed stationary-resource searching with predefined destinations under a multi-agent scenario. It is a distributed route planning problem with global optimization objectives. We present a probabilistic approach to achieving indirect resource coordination and latent agent cooperation in a distributed manner. Our approach treats the estimated availability of stationary resources as a reference and guides each agent based on their preferences. We evaluate our approach on four real-world datasets. Our approach outperforms state-of-the-art methods by 5% in multi-criteria optimization.
@inproceedings{10.1145/3589132.3625571,
author = {Lin, Fandel and Knoblock, Craig A.},
title = {Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations},
year = {2023},
isbn = {9798400701689},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3589132.3625571},
doi = {10.1145/3589132.3625571},
abstract = {Private vehicles are a direct means to bring people from one place to their desired destinations. However, no omniscient dispatcher is handling the origin-destination of vehicles and the availability of stationary resources, such as parking spaces or charging stations. Competitive cruising for stationary resources leads to environmental pollution and is a waste of drivers' time. We focus on the problem of distributed stationary-resource searching with predefined destinations under a multi-agent scenario. It is a distributed route planning problem with global optimization objectives. We present a probabilistic approach to achieving indirect resource coordination and latent agent cooperation in a distributed manner. Our approach treats the estimated availability of stationary resources as a reference and guides each agent based on their preferences. We evaluate our approach on four real-world datasets. Our approach outperforms state-of-the-art methods by 5\% in multi-criteria optimization.},
booktitle = {Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems},
articleno = {26},
numpages = {12},
keywords = {stationary-resource searching, distributed route planning, multi-criteria optimization},
location = {, Hamburg, Germany, },
series = {SIGSPATIAL '23}
}
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