Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151336
Title: Efficient decision-making for multiagent target searching and occupancy in an unknown environment
Authors: Yan, Fuhan
Di, Kai
Jiang, Jiuchuan
Jiang, Yichuan
Fan, Hui
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Yan, F., Di, K., Jiang, J., Jiang, Y. & Fan, H. (2019). Efficient decision-making for multiagent target searching and occupancy in an unknown environment. Robotics and Autonomous Systems, 114, 41-56. https://dx.doi.org/10.1016/j.robot.2019.01.017
Journal: Robotics and Autonomous Systems
Abstract: Target searching in an unknown environment is a traditional research issue in the multiagent area. In some real cases, the agents do not only discover the targets; instead, they have subsequent tasks that must be completed before a deadline. In this paper, these cases are abstracted as the agents searching for target locations in an unknown environment and then occupying these target locations within a limited time. The agents can obtain rewards by occupying the target locations, and the goal of this problem is to maximize net income, defined as total reward minus the moving cost of the agents. This problem can be transformed into the traditional problems, and then be solved by previous related algorithms. However, this approach is not optimal. In this paper, we present a method that combines previous algorithms and a decision-making algorithm. The experiments demonstrate that the method containing our decision-making algorithm can lead to higher net income than simply using previous algorithms.
URI: https://hdl.handle.net/10356/151336
ISSN: 0921-8890
DOI: 10.1016/j.robot.2019.01.017
Rights: © 2019 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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