Meet Powderworld: A Lightweight Simulation Environment For Understanding AI Generalization

Despite recent advances in RL research, the ability to generalize to new tasks remains one of the major issues in both reinforcement learning (RL) and decision-making. RL agents perform remarkably in a single-task setting but frequently make mistakes when faced with unforeseen obstacles. Additionally, single-task RL agents can largely overfit the tasks they are trained on, rendering them unsuitable for real-world applications. This is where a general agent that can successfully handle various unprecedented tasks and unforeseen difficulties can be useful. The vast majority of general agents are trained using a variety of diverse tasks. Recent deep-learning research has shown