AI reinforcement learning

DigiRL is an innovative online reinforcement learning algorithm for training intelligent agents capable of controlling devices in wild environments. It solves open-ended, real-world Android tasks through autonomous value assessment models (VLM). The main advantages of DigiRL include the ability to leverage existing non-optimal offline datasets and encourage agents to learn from their own trial and error through offline-to-online reinforcement learning. The model uses an instruction-level value function to implicitly build an automated course, prioritizing tasks that are most valuable to the agent, and picking out beneficial actions in the trajectory that contribute to the goal via a step-level value function.