MacroSwarm: A Field-based Compositional Framework for Swarm Programming
January 19, 2024 Β· Declared Dead Β· π International Conference on Coordination Models and Languages
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Authors
Gianluca Aguzzi, Roberto Casadei, Mirko Viroli
arXiv ID
2401.10969
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LO,
cs.SE
Citations
17
Venue
International Conference on Coordination Models and Languages
Last Checked
4 months ago
Abstract
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.
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