MacroSwarm：一个基于场的群体编程组合式框架
MacroSwarm: A Field-based Compositional Framework for Swarm Programming
AI总结：
本文提出基于场的组合式框架 MacroSwarm，将群体行为块表示为纯函数以映射感知场到致动目标场，通过模拟验证了其在群集、模式形成和集体决策中的表达力与自稳定弹性。
摘要：
群体行为工程是一个研究领域，旨在探索协调简单智能体群体内的计算与行动以实现复杂全局目标的方法和技术，这些目标包括模式形成、集体移动、聚类和分布式感知。尽管在群体（无人机、机器人、车辆）的分析与工程方面取得了近期进展，但仍然需要能够以有原则的方式定义复杂群体行为的通用设计、实现方法和工具。为了促进这一探索，本文提出了一种新的基于场的协调方法，称为 MacroSwarm，通过嵌入集体计算和协调的可重用且完全可组合的功能块来设计和编程群体行为。基于聚合计算的宏编程范式，MacroSwarm 的核心思想是将每个群体行为块表示为纯函数，将感知场映射为致动目标场，例如包含移动向量。为了展示 MacroSwarm 作为群体编程框架的表达能力、组合性和实用性，我们进行了多种模拟，涵盖了常见的群集、模式形成和集体决策模式。本文讨论了 MacroSwarm 中基于场计算的内在自稳定特性的意义，这些特性正式保证了某些弹性属性，并指导了该库的设计。
英文摘要：
Swarm behaviour engineering is an area of research that seeks to investigate methods and techniques for coordinating computation and action within groups of simple agents to achieve complex global goals like pattern formation, collective movement, clustering, and distributed sensing. Despite recent progress in the analysis and engineering of swarms (of drones, robots, vehicles), there is still a need for general design and implementation methods and tools that can be used to define complex swarm behaviour in a principled way. To contribute to this quest, this article proposes a new field-based coordination approach, called MacroSwarm, to design and program swarm behaviour in terms of reusable and fully composable functional blocks embedding collective computation and coordination. Based on the macroprogramming paradigm of aggregate computing, MacroSwarm builds on the idea of expressing each swarm behaviour block as a pure function, mapping sensing fields into actuation goal fields, e.g., including movement vectors. In order to demonstrate the expressiveness, compositionality, and practicality of MacroSwarm as a framework for swarm programming, we perform a variety of simulations covering common patterns of flocking, pattern formation, and collective decision-making. The implications of the inherent self-stabilisation properties of field-based computations in MacroSwarm are discussed, which formally guarantee some resilience properties and guided the design of the library.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
