2019-2020 Assessment of the Army Research Laboratory Interim Report (2020) / Chapter Skim
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2 Network and Information Sciences
2 Network and Information Sciences
Pages 12-23
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From page 12... ...
ARL research in information sciences seeks to develop new technologies that allow for information acquisition, analysis, reasoning and decision making, and assurance of information and knowledge. This research effort targets technological developments and enhancements that allow for efficient management of information in a dense data environment, extracting knowledge to deploy distributed intelligent systems, and to build effective systems for Multi-Domain Operations (MDO)
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From page 13... ...
The research review consisted of a number of presentations on topics such as learning from imitation, risk-aware learning, HDR saliency, and reinforcement learning for adaptable agents. There were also a number of poster presentations in these subject areas, including research on imitation from observation, semantic-based autonomous navigation, learned control policy, and information agents for value assessment.
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From page 14... ...
Such an approach can contribute to improved situational understanding. Virtual reality simulations were used to generate video data with motion parallax to train deep learning neural networks that will be tested against spatiotemporal test data.
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From page 15... ...
Although some interesting preliminary results have been generated, it would be important to clearly enunciate the rationale for the chosen approach, what competing strategies are possible, and whether the proposed approach performs better than existing solutions to this problem. Neural Network Models for Low-Resource and Morphologically Complex Language Processing This project is designed to improve the information extraction capabilities for morphologically complex languages such as Russian and Ukrainian by developing deep neural network-based morphological classifiers for such languages.
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From page 16... ...
The research on natural language processing was promising, and work related to application of multitask learning to small-corpus accented speech recognition is clearly an important area for research. The analysis of morphologically complex languages was creative and may fill a need -- competing approaches could be considered in this context.
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From page 17... ...
While not the focus of the ongoing work, this research could potentially also save communications bandwidth by the transmittal of the textual descriptions of the scenes instead of the full motion video. Low-Power, Low-Frequency Mobile Networking The goals and objectives of the project were to understand diverse communications modalities for more robust and covert operations, understand physical layer challenges and limitations, improve low probability of detection and low probability of intercept, and exploit autonomous agents that enhance networking capabilities and control radio radiation signatures.
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From page 18... ...
The validation of the approach with real vehicles lends additional credence to the results. Fog Computing and the Tactical Distributed Ledger These research projects represent two approaches to ensuring robust operation of a "network of things" such as cameras, directories, storage nodes, and so on, where the individual things fail, are replaced, or have degraded performance.
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From page 19... ...
The tactical distributed ledger stores state in multiple locations, and "smart contract" technology allows resources to advertise their application programming interfaces and permits nodes that require services from resources to be able to advertise their needs. The fog computing project is at an early stage of framing the overall concept.
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From page 20... ...
The portfolio of research would benefit from closer interaction between the two principal threads. For instance, there is the potential to use inverse reinforcement learning methods to aid in making narrative generation more personal and contextual.
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From page 21... ...
A stronger focus in areas like adversarial learning, integration of simulation in ML, and security related to ML would have provided a better understanding of the scope of ongoing work. As an example, simulation is emerging as a prominent element in training AI/ML systems, where physics-based simulation engines provide data to train autonomous vehicles and robots.
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From page 22... ...
In the area of human-robot interactions, advances in narrative generation are significant and have the potential of not only reducing soldier workload but also reducing the bandwidth requirement for tactical networks. The work related to active defense was considered to be exceptionally strong and provides a reduction in the cyber vulnerability of Army vehicles and other cyber-enabled systems.
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From page 23... ...
Recommendation: The Army Research Laboratory (ARL) should incorporate tactical network simulations such as the extendable mobile ad hoc network emulator, a next-generation framework for real-time modeling of mobile network systems, into its research program.
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