Cognitive Agent Evaluation for Synthetic Pilot Training

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0201240" target="_blank" >RIV/00216305:26230/26:0201240 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/11257300/keywords#keywords" target="_blank" >https://ieeexplore.ieee.org/document/11257300/keywords#keywords</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/dasc66011.2025.11257300" target="_blank" >10.1109/dasc66011.2025.11257300</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cognitive Agent Evaluation for Synthetic Pilot Training

Popis výsledku v původním jazyce

The utilization of Computer Generated Forces (CGFs) represents a valuable tool in facilitating the training, analysis and development of emerging technologies, particularly within the context of a Beyond Visual Range (BVR) encounters. In this paper, a cognitive model of a tactical pilot, based on the principles of Situational Awareness (SA) and used to represent authentic air forces in tactical training, is subjected to a unique multi-stage validation procedure that allows defining its suitability as a substitute for a human pilot in simulated operational scenarios. The proposed validation focuses on the analysis of information comprehension using Working Memory (WM) models for measured and synthesized flight deck scan patterns, including the non-parametric Kolmogorov-Smirnov test, with the aim of investigating the similarity of the scan duration distribution across a pair of eye fixation samples. The WM analysis also addresses the cell activation process in light of the latest cognitive science metrics. Finally, a tactical simulation framework for an iterative evaluation of authentic agent behavior is presented, confirming the importance of using a cognitive agent model with natural behavioral variability to increase the realism of simulated missions.

Název v anglickém jazyce

Cognitive Agent Evaluation for Synthetic Pilot Training

Popis výsledku anglicky

The utilization of Computer Generated Forces (CGFs) represents a valuable tool in facilitating the training, analysis and development of emerging technologies, particularly within the context of a Beyond Visual Range (BVR) encounters. In this paper, a cognitive model of a tactical pilot, based on the principles of Situational Awareness (SA) and used to represent authentic air forces in tactical training, is subjected to a unique multi-stage validation procedure that allows defining its suitability as a substitute for a human pilot in simulated operational scenarios. The proposed validation focuses on the analysis of information comprehension using Working Memory (WM) models for measured and synthesized flight deck scan patterns, including the non-parametric Kolmogorov-Smirnov test, with the aim of investigating the similarity of the scan duration distribution across a pair of eye fixation samples. The WM analysis also addresses the cell activation process in light of the latest cognitive science metrics. Finally, a tactical simulation framework for an iterative evaluation of authentic agent behavior is presented, confirming the importance of using a cognitive agent model with natural behavioral variability to increase the realism of simulated missions.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2025 AIAA DATC/IEEE 44th Digital Avionics Systems Conference (DASC)

ISBN

979-8-3315-2519-4

ISSN

—

e-ISSN

—

Počet stran výsledku

10

Strana od-do

1-10

Název nakladatele

IEEE

Místo vydání

Montreal, QC, Canada

Místo konání akce

Montreal

Datum konání akce

14. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001665766800122