Soft Actor-Critic in Lux AI Challenge Season 2: Optimizing Resource Collection and Lichen Growth Strategies with Advanced Data Science and Machine Learning

In Lux AI Challenge Season 2, this project uses a turn-based strategic game called Soft Actor-Critic (SAC). In a dynamic environment, SAC, a cutting-edge deep reinforcement learning algorithm, maximizes lichen growth and resource collec- tion. Building factories, cultivating lichen, and vying for resources in the 2D grid that forms the Lux universe requires strategic decision-making. A good option for handling the intricacies of the Lux game is the SAC algorithm because of its sample efficiency and stability. To provide insights into the application of sophisticated machine learning in strategic gaming scenarios, this endeavor investigates the performance of SAC, compares it with traditional methods, and makes proposed improvements.