Decision making with uncertainty using the LRM method: MATLAB versus Java

Dawn A. Lott; Adrienne Raglin; Somiya Metu

doi:10.1117/12.2585826

12 April 2021 Decision making with uncertainty using the LRM method: MATLAB versus Java

Dawn A. Lott, Adrienne Raglin, Somiya Metu

Proceedings Volume 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III; 117460B (2021) https://doi.org/10.1117/12.2585826
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

Challenges arise when sources of data are needed to provide information to teams of humans in multi-domain battle. Some critical challenges include the dependence and inter-dependence of heterogeneous devices and the uncertainty of information (UoI) obtained from these devices. UoI significantly affects the decision-making process and humans rely on underlying reasons for uncertainty in making decisions that rely on devices and data from these devices. The LRM Method is an excellent tool utilized to assist a decision-maker in support of military relevant operations. Previously, the LRM algorithm optimized the UoI and determined the decomposition of the UoI into its various elements via MATLAB. In recent work, the LRM algorithm is performed via Java. Although both algorithms compute the UoI to an error of within a negligible tolerance, there are small disparities in the decomposition of the UoI. Decomposing the UoI into its various parts is the main benefit of utilizing the LRM Method. These differences can have a significant impact on the decision-maker and the decision-making process.

Conference Presentation

Citation Download Citation

Dawn A. Lott, Adrienne Raglin, and Somiya Metu "Decision making with uncertainty using the LRM method: MATLAB versus Java", Proc. SPIE 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 117460B (12 April 2021); https://doi.org/10.1117/12.2585826

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