标题： 村民代理：一种基于图的多代理框架，用于协调Minecraft中的复杂任务依赖关系 显示英文标题

标题： VillagerAgent: A Graph-Based Multi-Agent Framework for Coordinating Complex Task Dependencies in Minecraft

摘要： 在本文中，我们旨在对多智能体系统进行评估，以应对复杂的依赖关系，包括空间、因果和时间约束。 首先，我们在Minecraft环境中构建了一个新的基准，名为VillagerBench。VillagerBench包含各种任务，旨在测试多智能体协作的各个方面，从工作负载分配到动态适应和同步任务执行。 其次，我们引入了一个有向无环图多智能体框架VillagerAgent，以解决复杂的智能体间依赖关系并提高协作效率。 该解决方案包括一个任务分解器，用于创建有向无环图（DAG）以进行结构化任务管理，一个智能体控制器用于任务分配，以及一个状态管理器用于跟踪环境和智能体数据。 我们在VillagerBench上的实证评估表明，VillagerAgent优于现有的AgentVerse模型，减少了幻觉并提高了任务分解的有效性。 结果强调了VillagerAgent在推进多智能体协作方面的潜力，在动态环境中提供了一个可扩展且通用的解决方案。 源代码在GitHub上开源（https://github.com/cnsdqd-dyb/VillagerAgent）。 显示英文摘要

摘要： In this paper, we aim to evaluate multi-agent systems against complex dependencies, including spatial, causal, and temporal constraints. First, we construct a new benchmark, named VillagerBench, within the Minecraft environment.VillagerBench comprises diverse tasks crafted to test various aspects of multi-agent collaboration, from workload distribution to dynamic adaptation and synchronized task execution. Second, we introduce a Directed Acyclic Graph Multi-Agent Framework VillagerAgent to resolve complex inter-agent dependencies and enhance collaborative efficiency. This solution incorporates a task decomposer that creates a directed acyclic graph (DAG) for structured task management, an agent controller for task distribution, and a state manager for tracking environmental and agent data. Our empirical evaluation on VillagerBench demonstrates that VillagerAgent outperforms the existing AgentVerse model, reducing hallucinations and improving task decomposition efficacy. The results underscore VillagerAgent's potential in advancing multi-agent collaboration, offering a scalable and generalizable solution in dynamic environments. The source code is open-source on GitHub (https://github.com/cnsdqd-dyb/VillagerAgent).