A novel distributed scheduling algorithm for time-critical multi-agent systems.
Conference item
Authors | Whitbrook, Amanda, Meng, Qinggang and Chung, Paul W. H. |
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Abstract | This paper describes enhancements made to the distributed performance impact (PI) algorithm and presents the results of trials that show how the work advances the state-of-the-art in single-task, single-robot, time-extended, multi-agent task assignment for time-critical missions. The improvement boosts performance by integrating the architecture with additional action selection methods that increase the exploratory properties of the algorithm (either soft max or e-greedy task selection). It is demonstrated empirically that the average time taken to perform rescue tasks can reduce by up to 8% and solution of some problems that baseline PI cannot handle is enabled. Comparison with the consensus-based bundle algorithm (CBBA) also shows that both the baseline PI algorithm and the enhanced versions are superior. All test problems center around a team of heterogeneous, autonomous vehicles conducting rescue missions in a 3-dimensional environment, where a number of different tasks must be carried out in order to rescue a known number of victims that is always more than the number of available vehicles. |
Keywords | Task allocation algorithms; Distributed task allocation; Multi-agent scheduling; Heuristic algorithms; Time critical scheduling |
Year | 2015 |
Journal | Proceedings of the International Conference on Intelligent Robots and Systems (IROS) |
Publisher | IEEE |
Digital Object Identifier (DOI) | https://doi.org/10.1109/IROS.2015.7354299 |
Web address (URL) | http://hdl.handle.net/10545/622387 |
hdl:10545/622387 | |
ISBN | 9781479999941 |
File | File Access Level Open |
Publication dates | 17 Dec 2015 |
Publication process dates | |
Deposited | 19 Mar 2018, 16:26 |
Contributors | Loughborough University |
https://repository.derby.ac.uk/item/93972/a-novel-distributed-scheduling-algorithm-for-time-critical-multi-agent-systems
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