Publication Details
Cognitive Modeling Approach for Generating Authentic Tactical Agent Behavior
Novák Jiří, Ing., Ph.D. (DCGM)
Chudý Peter, doc. Ing., Ph.D., MBA (VZ AeroWorks)
Aerial Encounter, Agent, Attention Model, Behavior Tree, Beyond Visual Range,
Cognition, Computer Generated Forces, Flight Dynamics, Long-Term Memory,
Nonlinear Model Predictive Control, Polynomial Chaos Expansion, Situational
Awareness, Tactical Simulation, Surrogate Modeling, Synthetic Training, Tactical
Autopilot, Working Memory
This paper presents a synthesis of a tactical cognitive agent that utilizes
advanced information processing models to enhance the human-like behavior of
Computer Generated Forces (CGFs). The agent's Situational Awareness (SA)
representation is enriched through the use of working memory, attention
synthesis, and decision-making based on machine-learned models to accurately
replicate human cognitive processes and behavior. This improved representation
allows the agent to demonstrate human-like behavior under increased workload,
a common condition in tactical flying scenarios. The innovative model structure
is based on established concepts in cognitive and neurosciences and implemented
using an Artificial Intelligence (AI) technique called the Behavior Tree (BT).
The execution of SA driven behavior utilizes a purposely designed tactical
autopilot based on Nonlinear Model Predictive Control (NMPC), enabling human-like
maneuver specification and validation. The resulting cognitive agent was
integrated into a ground-based simulation platform for synthetic tactical pilot
training.
@inproceedings{BUT189228,
author="Jiří {Hanák} and Jiří {Novák} and Peter {Chudý}",
title="Cognitive Modeling Approach for Generating Authentic Tactical Agent Behavior",
booktitle="AIAA/IEEE Digital Avionics Systems Conference - Proceedings",
year="2024",
volume="43",
number="9",
pages="1--15",
publisher="Institute of Electrical and Electronics Engineers",
address="San Diego",
doi="10.1109/DASC62030.2024.10749624",
isbn="979-8-3503-4961-0",
issn="2155-7195",
url="https://ieeexplore.ieee.org/document/10749624"
}