video1.0<iframe src="https://www.loom.com/embed/ce40d76ab8ec486ea6296c0f44829fed" frameborder="0" width="1152" height="864" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8641152Loomhttps://www.loom.com8641152https://cdn.loom.com/sessions/thumbnails/ce40d76ab8ec486ea6296c0f44829fed-00001.gif253.53333333333325In this video, I will be walking through my project demonstration for CS6376, my final term project. The project focuses on the comparative analysis of reinforcement learning and linear control methods for the inverted pendulum problem. I will showcase the GitHub repository where all the code can be found, and then dive into the two distinct parts of the project: the reinforcement learning (RL) part and the linear control part. I will explain the implementation of RL algorithms such as DQ learning, dual DQN, and single layer DQN, as well as the Q learning algorithm for the table. Additionally, I will demonstrate the implementation of the LQR algorithm in MATLAB for the linear control part. By the end of the video, you will have a clear understanding of the project and its results.