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DSDEVS-Based Simulation Acceleration with Event Filtering: USV Naval Combat Case
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AI
DOI：10.3390/systems13110979.png)
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Abstract
En 中文
This study presents a DSDEVS-based method to accelerate simulation execution for AI training in USV (Unmanned Surface vehicle) naval combat scenarios. The proposed approach introduces an event filtering technique that selectively suppresses low-importance sensing events based on the distance to enemy targets. By dynamically adjusting structural couplings and modifying sensing frequency through domain-specific thresholds, the method reduces execution time while maintaining a balance between speed and fidelity. Two key parameters-Event Filtering Distance (EFD) and Sensor Acceleration Time Advance (SATA)-enable conditional event filtering and time advance adjustments within the sensor model. Experimental results demonstrate a 3.03 improvement in runtime, highlighting the effectiveness of the method and the trade-off between simulation speedup and fidelity.
Keywords:
discrete event system
DEVS
DSDEVS
simulation for AI
simulation execution acceleration
unmanned surface vehicle simulation