Extending Data Farming for Multi-scale Decision Support by Integrating Novel AI Technologies Multi-Dimensional Data Farming

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NORTH ATLANTIC TREATY ORGANIZATION
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Extending Data Farming for Multi-scale Decision Support by
Integrating Novel AI Technologies
Multi-Dimensional
Data Farming:

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PUBLIC RELEASE 11/10/2023 | PAGE 2
BLUF
Multi-Dimensional Data Farming (MDDF) automates simulation decision-
making by the integration of innovative Artificial Intelligence (AI) Techniques
and allows improved and fast decisions in highly complex multi-scale, multi-
domain, and multi-level hybrid war campaigns.

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Data Farming
•Codified by MSG-088 Data Farming in Support of NATO
•The Realms of Data Farming (DF) collaboratively
connected by the DF Loop-of-Loops
•Characterization or Optimization
•NATO: Military Decision-Making
•Improved Situational Awareness
•Develop, analyze & refine COA
•Informed & robust decisions
•Proven and applied decision-support tool
•Limitations for large multi-scale campaigns with many factions and operations interacting at various levels

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Unconventional Campaign
•Blue & Green armed forces vs. Red fighting in physical &
cyber domains (s. RSY MSG-197 in Bath, GBR, 2022)
•Red launches a hybrid operation on Green, triggering a
Border Operation, in support of two strategic objectives:
•force Green to divert resources away from the Campaign
•lower Green public opinion in favor of the Campaign
•Strategic level: multi-faction multi-domain combat model
(Attrition, Cyber, Epidemic – ACE model)
•Tactical level: multi-agent based simulations of the Border Operation (Map Aware Non-uniform Automata,
MANA)

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Campaign Probability of Success
* alpha of supply for BLUE by GREEN

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Border Operation

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Embedding the Tactical Operation

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Accelerating Automation with AI
Explainable AI
Allows a broader range of meta-models to be considered without sacrificing interpretability
Automated Machine Learning
Increases the level of automation in building meta-models
Bayesian Optimization with Gaussian Processes
Framework to find optima of black-box functions

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DAVE (Design, Analyze & Visualize Experiments)
•Design of Experiments: Intelligent sequential search through COA space using meta-model predictions
•Analyze: Optimal balance of forces between Unconventional Campaign (UC) and Border Operation (BO)?
•Visualize: Temporal playback of UC, spatio-temporal playback of BO to gain insight

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DAVE Architecture & Implementation
•Based on and using Data Farming Services
(DFS) from MSG-155
•Dashboard + automized AI modules
•Implemented standalone for
PoC/Demonstrator, to be integrated later into
service-oriented architecture of DFS
•PoC status in 2023, extended to
Demonstrator for CWIX 2024

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DAVE Demo

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Summary
MDDF models for the first time the interplay of a long-time scale campaign and a short-time scale
operation, accounting for the complexity that arises in terms of time, sharing of resources and domains
involved.
MDDF shows how it is possible to combine AI techniques exploring operations at multiple scales (domain,
level, time) and optimize the probability of winning the campaign.
MDDF introduces a new multi-model approach to couple simulation models of different aggregations that
allow more comprehensive multi-level military planning and decision-making.
MDDF allows to accelerate the automation process making it efficient and effective in analyzing large and
complex multi-dimensional data spaces.
MDDF AI driven automation may extend the application of MDDF as a resource and time efficient
simulation support for wargaming in domains like mission support or training and education.

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PUBLIC RELEASE 11/10/2023 | PAGE 14
Chairs MSG-186 Multi-Dimensional Data Farming
FINLAND
LtCol, Dr. Esa Lappi
Esa.Lappi@mil.fi
GERMANY
LtCol Stephan Seichter
stephanseichter@bundeswehr.org
CANADA
Prof. Dr. Uyen Bao
p.bao.u.nguyen@gmail.com