This work introduces a novel framework for analyzing symbolic properties in deep reinforcement learning (DRL) agents, with applications in adaptive communication systems.
A preprint is available on arXiv: https://arxiv.org/abs/2604.04914
ACM SIGMETRICS 2026 Paper accepted
The paper "Analyzing Symbolic Properties for DRL Agents in Systems and Networking" by Zangooei et al. (a collaboration between the University of Waterloo and the Distributed Real-Time Systems Group) has been accepted for publication at ACM SIGMETRICS 2026.
Verfasst von JWe
