arXiv:2401.14461v1 [cs.AI] 25 Jan 2024 Page 1 Marabou 2.0: A Versatile Formal Analyzer of
Neural Networks Haoze Wu1, Omri Isac2, Aleksandar Zeljic1, Teruhiro Tagomori1,3, Matthew …

In recent years, Deep Reinforcement Learning (DRL) has become a popular paradigm in
machine learning due to its successful applications to real-world and complex systems …

Deep reinforcement learning (DRL) is a powerful machine learning paradigm for generating
agents that control autonomous systems. However, the" black box" nature of DRL agents …

In recent years, Machine Learning (ML) models have achieved remarkable success in
various domains. However, these models also tend to demonstrate unsafe behaviors …

In recent years, Explainable Artificial Intelligence (XAI) has attracted considerable attention
from the research community, primarily focusing on elucidating the opaque decision-making …

In recent years, Deep Reinforcement Learning (DRL) has emerged as an effective approach
to solving real-world tasks. However, despite their successes, DRL-based policies suffer …

Deep neural networks (DNNs) play a crucial role in the field of machine learning,
demonstrating state-of-the-art performance across various application domains. However …

In recent years, deep reinforcement learning (DRL) approaches have generated highly
successful controllers for a myriad of complex domains. However, the opaque nature of …

An exciting and promising frontier for Deep Reinforcement Learning (DRL) is its application
to real-world robotic systems. While modern DRL approaches achieved remarkable …