Dr. Daniel Javorsek Profile

Dr. Daniel Javorsek

at Defense Advanced Research Projects Agency

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Proceedings Article | 12 April 2021 Presentation + Paper

Context-sensitive, distributed, multi-domain adaptive option generation

M. Schneider, L. Barbulescu, L. Batlle-Rafferty, M. Cook, T. Kapler, M. Loppie, E. Pelletier, Z. Rubinstein, . Sexton, S. Smith, D. Javorsek

Proceedings Volume 11746, 1174608 (2021) https://doi.org/10.1117/12.2589944

KEYWORDS: Mars

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This paper presents how the combination of our Distributed InteRactivE C2 Tool (DIRECT) and Multi-Domain Adaptive Request Service (MARS) exploits underutilized resources through distributed adaptation of plans across domains. Deliberate planning processes, especially in the military, tend to be slow and unresponsive. Moreover, the introduction of more flexible assets such as multi-role aircraft introduces latent capacity that is often not exploited due to lack of flexible planning processes, thereby representing a significant opportunity to revolutionize the current system. We seek to overcome these challenges by enabling planners to respond to new requests during execution, through a semi-automated, distributed process that quickly generates options for adapting plans while meeting existing commitments, and presents them for human review. To accomplish this, we infer task state from reported mission states to simplify the manual process of tracking tasks and ensure that the adapted plan incorporates incomplete tasks but does not replan completed tasks. Our dynamic replanner generates options quickly, e.g., 316 seconds to adapt a plan with 345 missions to incorporate 1000 new tasks. This significantly increases utilization of resources, with 60%-70% of imagery requests for battle damage assessment being satisfied by multi-role fighters already flying. Finally, we provide options in context of the existing plan through adaptive option ranking that promotes options that meet operator preferences as judged from abstract evaluation factors designed to apply across different domains. The ranking achieves 80% accuracy for predicting the top option, presenting the preferred option to the operator the vast majority of the time.

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