1. Minitrack Introduction: Decision Analytics, Machine Learning, and Field Experimentation for Defense and Emergency Response
- Author
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Bordetsky, Alex, Mullins, Steven J., Hudgens, Bryan J., and Naval Postgraduate School
- Abstract
Proceedings of the 54th Hawaii International Conference on System Sciences 2021 The article of record as published may be found at http://http://hdl.handle.net/10125/70746 Defense and emergency first responders must make rapid, consequential decisions and machine learning can aid analytics to support these decisions. Machine learning offers enormous promise, yet well publicized struggles reveal the need for better datasets and for opportunities to learn in challenging settings. Field experimentation offers the potential to meet these needs through iterative interactions in complex scenarios. Field experimentation can provide live action to facilitate high fidelity datasets that can support machine learning and artificial/augmented intelligence applications. These experiments may incorporate participants from academia; government agencies; militaries; first responders at all levels; and global industry partners. This minitrack explores the interplay between machine learning, field experimentation, and optimization analytics, whether exploratory, theoretical, experimental, in such critical areas as Defense and Emergency Response.
- Published
- 2021