Hayfaa Subhi Malallah

An Automated Framework for Self-Adaptive Quality Assurance in Software Systems Using Policy-Based Reinforcement Learning

This paper presents a framework that removes both limits by using policy-based RL, and improves on a value-based baseline (DQN) with statistical significance and performs on par with a maximum-entropy method (SAC) under the tested settings, while keeping good sample efficiency and stability.