Exploring Deep Reinforcement Learning Models

As part of a school project, I delved into the fascinating world of Deep Q-Learning, experimenting with various models, including DQN (Deep Q-Network) and DDPG (Deep Deterministic Policy Gradient).

My focus was on optimizing hyperparameters within the Pendulum v1 gym environment, where I analyzed the effects of different configurations on the agent's performance.

This hands-on experience not only deepened my understanding of reinforcement learning algorithms but also honed my skills in model tuning and performance evaluation, making it a rewarding learning journey. I am proud to have attained distinctions for this module overall