Name
Title | ||
|---|---|---|
Fusing uncertain knowledge and evidence for maritime situational awareness via Markov Logic Networks |
Abstract | ||
|---|---|---|
The concepts of event and anomaly are important building blocks for developing a situational picture of the observed environment. We here relate these concepts to the JDL fusion model and demonstrate the power of Markov Logic Networks (MLNs) for encoding uncertain knowledge and compute inferences according to observed evidence. MLNs combine the expressive power of first-order logic and the probabilistic uncertainty management of Markov networks. Within this framework, different types of knowledge (e.g. a priori, contextual) with associated uncertainty can be fused together for situation assessment by expressing unobservable complex events as a logical combination of simpler evidences. We also develop a mechanism to evaluate the level of completion of complex events and show how, along with event probability, it could provide additional useful information to the operator. Examples are demonstrated on two maritime scenarios of rules for event and anomaly detection. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.inffus.2013.03.004 | Information Fusion |
Keywords | Field | DocType |
context-based fusion,markov logic networks,situational awareness,uncertainty management | Anomaly detection,Descriptive knowledge,Situation awareness,Markov chain,A priori and a posteriori,Situation analysis,Artificial intelligence,Probabilistic logic,Unobservable,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
21, | 1566-2535 | 18 |
PageRank | References | Authors |
0.73 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lauro Snidaro | 1 | 185 | 20.90 |
| Ingrid Visentini | 2 | 74 | 7.43 |
| Karna Bryan | 3 | 107 | 6.94 |