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. 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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