Part 5/9:
This was evidenced by the AI efficiently managing the increasingly intricate game layout, adeptly eating fruits while avoiding randomly placed traps. An even bolder request was made next: creating a deep learning model that utilized reinforcement learning concepts—essentially allowing the AI to improve through trial and error.
Building a Machine Learning Model
Upon receiving instructions to implement reinforcement learning, the AI executed with remarkable speed and intelligence. It outlined a potential solution while defining key concepts involved in crafting such an environment. By suggesting techniques such as positive and negative reward mechanisms for actions taken during gameplay, the model displayed an understanding of fundamental machine learning principles.