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MinePlanner: A Benchmark for Long-Horizon Planning in Large Minecraft Worlds

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arxiv 2312.12891 v2 pith:AZO6HHJD submitted 2023-12-20 cs.AI

classification cs.AI
keywords benchmarktasksminecraftplanninginstancesnumericplannerspropositional
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. WGSR-Bench: Wargame-based Game-theoretic Strategic Reasoning Benchmark for Large Language Models

    cs.AI 2025-06 conditional novelty 6.0 of 10

    A new wargame-based benchmark finds large language models score far below human experts on strategic reasoning across situation awareness, opponent modeling, and policy generation.

  2. TextAtari: 100K Frames Game Playing with Language Agents

    cs.CL 2025-06 conditional novelty 5.0 of 10

    TextAtari is a text-based Atari benchmark for language agents; 7-8B LLMs stay below 10% of human scores in over 90% of tested conditions, and knowledge injection helps more than chain-of-thought.

  3. Large Language Models for Planning: A Comprehensive and Systematic Survey

    cs.AI 2025-05 conditional novelty 3.0 of 10

    A structured survey of LLM planning methods, benchmarks, and interpretability work, organized around a three-way taxonomy.

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