Max-sum for allocation of changing cost tasks

James Parker, Alessandro Farinelli, Maria Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


We present a novel decentralized approach to allocate agents to tasks whose costs increase over time. Our model accounts for both the natural growth of the tasks and the effort of the agents at containing such growth. The objective is to minimize the increase in task costs. We show how a distributed coordination algorithm, which is based on max-sum, can be formulated to include costs of tasks that grow over time. Considering growing costs enables our approach to solve a wider range of problems than existing methods. We compare our approach against state-of-the-art methods in both a simple simulation and RoboCup Rescue simulation.

Original languageEnglish (US)
Title of host publicationIntelligent Autonomous Systems 14 - Proceedings of the 14th International Conference IAS-14
EditorsWeidong Chen, Hesheng Wang, Koh Hosoda, Emanuele Menegatti, Masahiro Shimizu
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319480350
StatePublished - 2017
Event14th International Conference on Intelligent Autonomous Systems, IAS 2016 - Shanghai, China
Duration: Jul 3 2016Jul 7 2016

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


Other14th International Conference on Intelligent Autonomous Systems, IAS 2016
City Shanghai

Bibliographical note

Funding Information:
Work supported in part by NSF-IIP-1439728 and the Graduate School of the University of Minnesota.

Publisher Copyright:
© Springer International Publishing AG 2017.


  • Binary max-sum
  • Multi-robot systems
  • Task allocation


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