4 papers
Interpretable Attention-Based Multi-Agent PPO for Latency Spike Resolution in 6G RAN Slicing
Kavan Fatehi, Mostafa Rahmani Ghourtani, Amir Sonee +4
Sixth-generation (6G) radio access networks (RANs) must enforce strict service-level agreements (SLAs) for heterogeneous slices, yet sudden latency spikes remain difficult to diagn…
Preliminary Investigation into Uncertainty-Aware Attack Stage Classification
Alessandro Gaudenzi, Lorenzo Nodari, Lance Kaplan +3
Advanced Persistent Threats (APTs) represent a significant challenge in cybersecurity due to their prolonged, multi-stage nature and the sophistication of their operators. Traditio…
Learning Robust Reward Machines from Noisy Labels
Roko Parac, Lorenzo Nodari, Leo Ardon +3
This paper presents PROB-IRM, an approach that learns robust reward machines (RMs) for reinforcement learning (RL) agents from noisy execution traces. The key aspect of RM-driven R…
FORM: Learning Expressive and Transferable First-Order Logic Reward Machines
Leo Ardon, Daniel Furelos-Blanco, Roko Parac +1
Reward machines (RMs) are an effective approach for addressing non-Markovian rewards in reinforcement learning (RL) through finite-state machines. Traditional RMs, which label edge…