Adaptable System for Disaggregated Distributed AI Chat Enablement (D2ACE) to Support Mission Engineering.
Saved in:
| Title: | Adaptable System for Disaggregated Distributed AI Chat Enablement (D2ACE) to Support Mission Engineering. |
|---|---|
| Authors: | Hershey, Paul C.1 (AUTHOR) paul.c.hershey@rtx.com, Wang, Mu‐Cheng1 (AUTHOR), Coston, Jennifer N.1 (AUTHOR), Ryan, Jennifer L.1 (AUTHOR), Scarpiniti, Brian D.1 (AUTHOR), Kabalkin, Darin G.1 (AUTHOR), Horner, Christopher R.1 (AUTHOR) |
| Source: | Systems Engineering. Sep2025, Vol. 28 Issue 5, p640-647. 8p. |
| Subjects: | Artificial intelligence, Distributed artificial intelligence, Systems engineering, Real-time programming, Communication planning, Security management, Instant messaging |
| Abstract: | This paper presents an adaptable system for disaggregated and distributed chat communications that applies Artificial Intelligence (AI) to support time‐critical battlespace environments. In such environments, operators may have dozens of chat conversations ongoing simultaneously. Although some of these messages are sorted according to keywords to help the operators better prioritize them, these keywords are subject to typing errors and other corruptions that may lead to the operator missing key decision‐making information. Considering the present expansion of the battlespace to include multimission and multidomain, the number of chat sessions is greatly increasing. The challenge for mission engineering in this environment is how to reduce and prioritize the vastly expanding collection of chat messages so that operators focus only on those chat messages that are most critical to meeting mission success and to do so accurately and dynamically. The approach presented here introduces a real‐time tasking capability within a fully autonomous adaptable system for Disaggregated Distributed AI Chat Enablement (D2ACE) to support mission engineering. D2ACE applies AI/ML techniques to correct spelling, typos, and other corruptions in chat messages; to adapt to recognize uncommon language formats; and to prioritize and reduce the quantity of chat messages to only those relevant to specific commander's objectives and intent for the mission. D2ACE accomplishes these goals while maintaining security at a high level such that only authorized individuals have access to their respective relevant chat messages. [ABSTRACT FROM AUTHOR] |
| Copyright of Systems Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | This paper presents an adaptable system for disaggregated and distributed chat communications that applies Artificial Intelligence (AI) to support time‐critical battlespace environments. In such environments, operators may have dozens of chat conversations ongoing simultaneously. Although some of these messages are sorted according to keywords to help the operators better prioritize them, these keywords are subject to typing errors and other corruptions that may lead to the operator missing key decision‐making information. Considering the present expansion of the battlespace to include multimission and multidomain, the number of chat sessions is greatly increasing. The challenge for mission engineering in this environment is how to reduce and prioritize the vastly expanding collection of chat messages so that operators focus only on those chat messages that are most critical to meeting mission success and to do so accurately and dynamically. The approach presented here introduces a real‐time tasking capability within a fully autonomous adaptable system for Disaggregated Distributed AI Chat Enablement (D2ACE) to support mission engineering. D2ACE applies AI/ML techniques to correct spelling, typos, and other corruptions in chat messages; to adapt to recognize uncommon language formats; and to prioritize and reduce the quantity of chat messages to only those relevant to specific commander's objectives and intent for the mission. D2ACE accomplishes these goals while maintaining security at a high level such that only authorized individuals have access to their respective relevant chat messages. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 10981241 |
| DOI: | 10.1002/sys.21813 |
