Multi-agent ad hoc systems are dynamic collaborative systems in which multiple autonomous agents must cooperate with both known and unknown teammates in open environments, without relying on pre-coordinated strategies. These systems operate under conditions of uncertainty and partial observability, where team composition, agent behaviors, and environmental factors may change during execution. Through an analysis of information flow in such systems, we identify two key limitations in existing research: insufficient information flow and limited information processing capacity. To address these issues, we propose an information flow structure for multi-agent ad hoc systems (IFS), which tackles these challenges from the perspectives of communication and information fusion. Experimental results in StarCraft II demonstrate that IFS significantly improves both information flow and processing capacity, while exhibiting strong generalization capabilities and outperforming baseline methods in complex ad hoc teamwork scenarios.
翻译:多智能体自组织系统是一种动态协作系统,其中多个自主智能体必须在开放环境中与已知和未知的队友合作,且不依赖于预先协调的策略。这些系统在不确定性和部分可观测性的条件下运行,其团队构成、智能体行为和环境因素在执行过程中可能发生变化。通过对此类系统中信息流的分析,我们指出了现有研究中的两个关键局限:信息流不足与信息处理能力有限。为解决这些问题,我们提出了一种用于多智能体自组织系统的信息流结构(IFS),该结构从通信和信息融合的角度应对这些挑战。在《星际争霸II》中的实验结果表明,IFS显著提升了信息流与信息处理能力,同时在复杂的自组织协作场景中展现出强大的泛化能力,并优于基线方法。