Co-Optimization Multi-Agent Placement with Task Assignment and Scheduling

TitleCo-Optimization Multi-Agent Placement with Task Assignment and Scheduling
Publication TypeConference Proceedings
Year of Conference2016
AuthorsZhang, C., and J. A. Shah
Conference NameInternational Joint Conference on Artificial Intelligence (IJCAI)
Date Published07/2016
AbstractTo enable large-scale multi-agent coordination under temporal and spatial constraints, we formulate it as a multi-level optimization problem and develop a multi-abstraction search approach for cooptimizing agent placement with task assignment and scheduling. This approach begins with a highly abstract agent placement problem and the rapid computation of an initial solution, which is then improved upon using a hill climbing algorithm for a less abstract problem; finally, the solution is fine-tuned within the original problem space. Empirical results demonstrate that this multi-abstraction approach significantly outperforms a conventional hill climbing algorithm and an approximate mixed integer linear programming approach
URLhttps://interactive.mit.edu/sites/default/files/documents/Zhang_IJCAI16.pdf
Refereed DesignationRefereed