Answers are grounded in this paper and cite their sources.
Computational modeling demonstrates real-time threat assessment for underwater vehicles in congested waters, highlighting robust uncertainty reasoning using credal sets and probability mass functions.
The paper develops a valuation based system for reasoning under uncertainty in the context of threat assessment onboard an underwater vehicle. The focus is on threat posed by the nearby contacts, while the vessel is navigating busy waters with warships, merchant ships and fishing vessels. A graphical model of a valuation network is developed, representing the (uncertain) contextual prior knowledge and received observations over the course of time. Two types of valuations are considered in this context: (1) probability mass functions, assuming that all probabilistic values are known precisely; (2) credal sets (sets of probabilities), when probabilistic values are specified only as the confidence intervals. The performance of two valuation networks is presented, using a typical scenario-log, involving a varying number of different types of contacts over time.
No takes yet. Share an insight, caveat, or question.
Ristić et al. (2024) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: