Polycraft World AI Lab (PAL): An Extensible Platform for Evaluating Artificial Intelligence Agents
This provides a versatile and extensible platform for AI researchers to evaluate agents in open-world environments, though it is incremental as it builds on existing Minecraft mods.
The paper tackles the need for adaptable platforms to evaluate AI agents by presenting the Polycraft World AI Lab (PAL), a task simulator based on Minecraft, which enables flexible task creation and logging of agent actions, with evaluations demonstrated on multi-step planning and navigation tasks.
As artificial intelligence research advances, the platforms used to evaluate AI agents need to adapt and grow to continue to challenge them. We present the Polycraft World AI Lab (PAL), a task simulator with an API based on the Minecraft mod Polycraft World. Our platform is built to allow AI agents with different architectures to easily interact with the Minecraft world, train and be evaluated in multiple tasks. PAL enables the creation of tasks in a flexible manner as well as having the capability to manipulate any aspect of the task during an evaluation. All actions taken by AI agents and external actors (non-player-characters, NPCs) in the open-world environment are logged to streamline evaluation. Here we present two custom tasks on the PAL platform, one focused on multi-step planning and one focused on navigation, and evaluations of agents solving them. In summary, we report a versatile and extensible AI evaluation platform with a low barrier to entry for AI researchers to utilize.