Collectiveness is an important property of many systems—both natural and artificial. By
exploiting a large number of individuals, it is often possible to produce effects that go far …

Recent trends in pervasive computing promote the vision of Collective Adaptive Systems
(CASs): large-scale collections of relatively simple agents that act and coordinate with no …

Swarm behaviour engineering is an area of research that seeks to investigate methods for
coordinating computation and action within groups of simple agents to achieve complex …

In recent years, the infrastructure supporting the execution of situated distributed
computations evolved at a fast pace. Modern collective adaptive applications–as found in …

Distributed collective systems are systems formed by homogeneous dynamic collections of
devices acting in a shared environment to pursue a joint task or goal. Typical applications …

This article introduces ScaRLib, a Scala-based framework that aims to streamline the
development cyber-physical swarms scenarios (ie, systems of many interacting distributed …

The edge–cloud continuum provides a heterogeneous, multi-scale, and dynamic
infrastructure supporting complex deployment profiles and trade-offs for application …

The Internet of Things (IoT) and edge computing are fostering a future of ecosystems hosting
complex decentralized computations that are deeply integrated with our very dynamic …

In recent advancements in machine learning, federated learning allows a network of
distributed clients to collaboratively develop a global model without needing to share their …

Macro-programming enables the definition of highly distributed applications as a single
“macro-program”, providing first-class abstractions to describe and reason about global …