On January 17, CSIE Research Assistant Andy Younes presented a seminar on advancements in reinforcement learning, focusing on the SAC (Soft Actor-Critic) algorithm and its applications to real-world robotics tasks.

The seminar addressed key challenges in deep reinforcement learning, including high sample complexity and sensitivity to hyperparameters. Andy explored how SAC's maximum entropy framework achieves state-of-the-art performance in challenging domains such as quadrupedal locomotion and robotic manipulation.

About the Speaker: Andy Younes is a Research Assistant at CSIE specializing in machine learning and control systems. She completed her Bachelor's degree in Software Engineering from NPUA in 2024. Andy has contributed to several research projects, including the development of a machine learning algorithm for deblurring, denoising, and colorizing old images. Recently, she led a team to a third-place finish in the 2024 American Control Conference Self-Driving Car Student Competition.