Training Agent

Training agents, primarily within the framework of reinforcement learning, aims to create artificial intelligence capable of making optimal decisions within complex environments. Current research emphasizes improving agent learning through techniques like world dynamics modeling, aligning agent behavior using methods analogous to large language model alignment, and leveraging diverse data sources for more robust and generalizable performance. This field is significant for advancing AI capabilities in diverse applications, from robotics and game playing to more complex tasks like web navigation and power grid control, with a growing focus on interpretability and efficient training methods.