MinePlanner: A Benchmark for Long-Horizon Planning in Large Minecraft Worlds
William Hill, Ireton Liu, Anita De Mello Koch, Damion Harvey, Nishanth, Kumar, George Konidaris, Steven James

TL;DR
This paper introduces MinePlanner, a comprehensive benchmark for long-horizon planning in large Minecraft worlds, highlighting current planner limitations and guiding future improvements.
Contribution
It presents a new benchmark with 45 tasks for Minecraft planning, supporting automatic creation of propositional and numeric instances, and evaluates existing planners on these tasks.
Findings
State-of-the-art planners struggle with large-scale Minecraft tasks.
Current planners cannot handle instances with thousands of objects.
The benchmark reveals specific challenges and areas for future research.
Abstract
We propose a new benchmark for planning tasks based on the Minecraft game. Our benchmark contains 45 tasks overall, but also provides support for creating both propositional and numeric instances of new Minecraft tasks automatically. We benchmark numeric and propositional planning systems on these tasks, with results demonstrating that state-of-the-art planners are currently incapable of dealing with many of the challenges advanced by our new benchmark, such as scaling to instances with thousands of objects. Based on these results, we identify areas of improvement for future planners. Our framework is made available at https://github.com/IretonLiu/mine-pddl/.
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Taxonomy
TopicsAI-based Problem Solving and Planning · Logic, Reasoning, and Knowledge · Artificial Intelligence in Games
