Autonomic computing aims to deal with the complexity of todays systems by letting the system handle the complexity autonomously. This is a very hard and challenging domain because current systems are complex, distributed, interconnected and rapidly changing systems. We firmly belief that a main challenge in conquering autonomic systems is the integration of three existing research communities: the multi-agent systems community allows natural modelling of the system and explicitly considers autonomous behaviour and distributed interaction, dynamical systems theory allows analysis of the dynamics of these models and the decentralised control community can use insights gathered from the analysis to create decentralised control mechanisms to control the dynamics of autonomic systems. This paper describes this generic perspective on autonomic computing, gives an overview of the relevant work done in each community and describes the contribution of each community in conquering autonomic computing.

When designing decentralised autonomic computing systems, a fundamental engineering issue is to assess system-wide behaviour. Such decentralised systems are characterised by the lack of global control, typically consist of autonomous cooperating entities, and often rely on self-organised emergent behaviour to achieve the requirements. A well-founded and practically feasible approach to study overall system behaviour is a prerequisite for successful deployment. On one hand, formal proofs of correct behaviour and even predictions of the exact system-wide behaviour are practically infeasible due to the complex, dynamic, and often non-deterministic nature of self-organising emergent systems. On the other hand, simple simulations give no convincing arguments for guaranteeing system-wide properties. We describe an alternative approach that allows to analyse and assess trends in system-wide behaviour, based on so-called “equation-free” macroscopic analysis. This technique yields more reliable results about the system-wide behaviour, compared to mere observation of simulation results, at an affordable computational cost. Numerical algorithms act at the system-wide level and steer the simulations. This allows to limit the amount of simulations considerably. We illustrate the approach by studying a particular system-wide property of a decentralised control system for Automated Guided Vehicles and we outline a road map towards a general methodology for studying decentralised autonomic computing systems.

Claytronics is a form a programmable matter that takes the concept of modular robots to a new extreme. The concept of modular robots has been around for some time. (See [14] for a survey.) Previous approaches to modular robotics sought to create an ensemble of tens or even hundreds of small autonomous robots which could, through coordination, achieve a global effect not possible by any single unit. In general the goal of these projects was to adapt to the environment to facilitate, for example, improved locomotion. Our work on claytronics departs from previous work in several important ways. One of the primary goals of claytronics is to form the basis for a new media type, pario. Pario, a logical extension of audio and video, is a media type used to reproduce moving 3D objects in the real world. A direct result of our goal is that claytronics must scale to millions of micron-scale units. Having scaling (both in number and size) as a primary design goal impacts the work significantly.