@inproceedings{f0839cb1667741c9a336df4261152fce,
title = "Heuristics on the data-collecting robot problem with immediate rewards",
abstract = "We propose the Data-collecting Robot Problem, where robots collect data as they visit nodes in a graph, and algorithms to solve it. There are two variations of the problem: the delayed-reward problem, in which robots must travel back to the base station to deliver the data collected and to receive rewards; and the immediate-reward problem, in which the reward is immediately given to the robots as they visit each node. The delayed-reward problem is discussed in one of the authors{\textquoteright} work. This paper focuses on the immediate-reward problem. The solution structure has a clustering step and a tour-building step. We propose Progressive Gain-aware Clustering that finds good quality solutions with efficient time complexity. Among the six proposed tourbuilding heuristics, Greedy Insertion and Total-Loss algorithms perform best when data rewards are different.",
keywords = "Adversary route planning, Autonomous systems, Multi-robot systems",
author = "Zhi Xing and Oh, {Jae C.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 19th International Conference on Princiles and Practice of Multi-Agent Systems, PRIMA 2016 ; Conference date: 22-08-2016 Through 26-08-2016",
year = "2016",
doi = "10.1007/978-3-319-44832-9_8",
language = "English (US)",
isbn = "9783319448312",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "131--148",
editor = "Matteo Baldoni and Katsutoshi Hirayama and Paolo Torroni and Son, {Tran Cao} and Chopra, {Amit K.}",
booktitle = "Princiles and Practice of Multi-Agent Systems - 19th International Conference, PRIMA 2016, Proceedings",
}