A multimodel approach to modeling intelligent combat behaviors for wargaming

Scotty E. Black; Christian J. Darken

doi:10.1117/12.3015088

7 June 2024 A multimodel approach to modeling intelligent combat behaviors for wargaming

Scotty E. Black, Christian J. Darken

Proceedings Volume 13051, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI; 130510R (2024) https://doi.org/10.1117/12.3015088
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Remaining competitive in future conflicts with technologically-advanced competitors requires us to accelerate the development of robust artificial intelligence (AI) for wargaming. In this study, we contribute to the research of AI methods to develop intelligent agent behaviors in combat simulations by investigating the effectiveness of a multi-model approach as compared to a single-model approach. To accomplish this, we first develop a multi-model framework that leverages supervised learning, reinforcement learning, and scripted behavior models. We then design and conduct an experiment where we compare the performance of each one of eight individual behavior models to four multi-models composed of varying numbers of these individual behavior models. Using a combat simulation with a random scenario generator, we find that a multi-model approach improved the mean score by 62.6% over the mean game score of the best-performing single-model. Additionally, we find that a multi-model with more embedded behavior models outperforms a multi-model with fewer behavior models. The outcomes of this study contribute to the broader research endeavors aimed at expanding AI capabilities to handle the intricate and expansive state-spaces characteristic of combat modeling and simulation.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Scotty E. Black and Christian J. Darken "A multimodel approach to modeling intelligent combat behaviors for wargaming", Proc. SPIE 13051, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI, 130510R (7 June 2024); https://doi.org/10.1117/12.3015088

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available