Information Networks: RESUME: Artificial Intelligence, Algorithms, and Optimization for Responsible Reopening
Abstract
In the face of COVID-19, entities ranging from businesses to universities to military units must adapt how their members work and interact. Not all risk can be avoided, but careful planning and scheduling can strike a good balance between risk experienced and the value of the work done. This generally involves assigning individuals both to shifts and to specific locations. Generally, these problems correspond to computationally hard optimization problems, making it unlikely that people can solve them well by inspection. We propose a unified framework called RESUME for these optimization problems. The general framework allows one to model the value generated by having individuals work together, limitations on resources and physical locations, and constraints on how all these can be deployed together. This framework leads to a number of research challenges in the design of algorithms for this framework as well as the testing and evaluation of those algorithms. We propose to address these challenges by combining techniques from artificial intelligence, graph algorithms, and optimization, and to evaluate the techniques theoretically, in simulations, and on real data that we will gather. This work will significantly advance the scientific state-of-the-art in areas including artificial intelligence, multiagent systems, and graph algorithms. Specifically, it will result in new algorithms for these types of combinatorial problems, theoretical guarantees for such algorithms, evaluations in simulations for such algorithms, and new methods to test such algorithms on real data. The project also has the potential to generate direct value in helping entities to reopen responsibly and effectively, contributing to public safety, security, and productivity.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 25, 2021
- Source ID
- W911NF2110230
Entities
People
- Vincent Conitzer
Organizations
- Army Contracting Command
- Duke University
- United States Army