多智能体协同效率评测数据集

本数据集聚焦多智能体协同效率的量化评测，覆盖分布式搜索、资源运输、协同感知、分布式约束满足、协同决策等任务类型。数据内容包括任务场景参数（智能体数量、任务数量、通信拓扑、动态性）、智能体配置（异构性、感知范围、带宽）、协同策略算法（集中式、拍卖、共识、MARL）及其超参数、执行效率指标（完成时间、响应时间、吞吐量、通信开销、负载均衡、成功率）。适用于协同算法对比、通信开销分析、自适应策略优化、容量规划及效率预测模型训练等场景。This dataset focuses on the quantitative evaluation of multi-agent collaboration efficiency, covering task types including distributed search, resource transportation, collaborative perception, distributed constraint satisfaction, collaborative decision-making, etc. Its data content includes task scenario parameters (number of agents, number of tasks, communication topology, environmental dynamics), agent configurations (heterogeneity, perception range, communication bandwidth), collaboration strategy algorithms (centralized, auction, consensus, MARL) and their hyperparameters, as well as execution efficiency metrics (completion time, response time, throughput, communication overhead, load balancing, success rate). It is applicable to scenarios such as collaborative algorithm comparison, communication overhead analysis, adaptive strategy optimization, capacity planning, and efficiency prediction model training.

搜集汇总

背景与挑战

背景概述

该数据集专用于量化评估多智能体系统的协同效率，覆盖分布式搜索、资源运输、协同感知等多种任务类型，并包含任务场景参数、智能体配置、协同策略及执行效率指标。它适用于协同算法对比、通信开销分析、策略优化以及效率预测模型训练等研究与应用场景，数据规模为1TB，属于软件和信息技术服务业的具身智能领域。