CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Tasks

• URL: http://arxiv.org/abs/2508.18797v1
• Date: Tue, 26 Aug 2025 08:29:05 GMT
• Title: CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Tasks
• Authors: Qi Chai, Zhang Zheng, Junlong Ren, Deheng Ye, Zichuan Lin, Hao Wang,
• Abstract summary: We propose CausalMACE, a holistic causality planning framework designed to enhance multi-agent systems.<n>Our proposed framework introduces two modules: an overarching task graph for global task planning and a causality-based module for dependency management.<n> Experimental results demonstrate our approach achieves state-of-the-art performance in multi-agent cooperative tasks of Minecraft.
• Score: 16.633868216217948
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Minecraft, as an open-world virtual interactive environment, has become a prominent platform for research on agent decision-making and execution. Existing works primarily adopt a single Large Language Model (LLM) agent to complete various in-game tasks. However, for complex tasks requiring lengthy sequences of actions, single-agent approaches often face challenges related to inefficiency and limited fault tolerance. Despite these issues, research on multi-agent collaboration remains scarce. In this paper, we propose CausalMACE, a holistic causality planning framework designed to enhance multi-agent systems, in which we incorporate causality to manage dependencies among subtasks. Technically, our proposed framework introduces two modules: an overarching task graph for global task planning and a causality-based module for dependency management, where inherent rules are adopted to perform causal intervention. Experimental results demonstrate our approach achieves state-of-the-art performance in multi-agent cooperative tasks of Minecraft.

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