Polycraft World AI Lab (PAL): An Extensible Platform for Evaluating Artificial Intelligence Agents
Stephen A. Goss, Robert J. Steininger, Dhruv Narayanan, Daniel V. Olivença, Yutong Sun, Peng Qiu, Jim Amato, Eberhard O. Voit, Walter E. Voit, Eric J. Kildebeck
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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.