Modern systems are often structured as complex, multi-layered networks of interconnected parts, where different layers interact and influence each other in intricate and sometimes unforeseen ways. It is infeasible for human operators to constantly monitor these interactions and to adjust the system to cope with unexpected circumstances; instead systems have to adapt autonomously to dynamically changing situations while still respecting their design constraints and requirements. Because of the distributed and decentralized nature of modern systems, this usually has to be achieved by collective adaptation of the nodes comprising the system. In open systems exhibiting collective adaptation, unforeseen events and properties can arise, e.g. as side effects of the interaction of the components or the environment. Modelling and engineering collective adaptive systems has to take into account such "emergent" properties in addition to satisfying functional and quantitative requirements.

Finding ways to understand and design collective adaptive systems, and to predict their behaviour, is a difficult but important endeavour. One goal of this seminar is to investigate techniques for modelling and analysing systems that adapt collectively to dynamically changing environment conditions and requirements. In many cases, these models and analysis techniques should not only capture qualitative properties of the system, such as absence of deadlocks, they should also be able to express quantitative properties such as quality of service.

Research on collective adaptive systems builds on and integrates previous research efforts from several areas:

Formal foundations and modelling techniques for concurrent systems deal with problems such as enabling and limiting concurrency, access to shared resources, avoidance of anomalies, communication between processes, and estimation of performance.
Analysis of concurrent systems typically exploits such notions as bisimilarity of different processes or reasons on stochastic properties of systems consisting of many equivalent processes.
The area of adaptive systems also investigates systems consisting of interacting entities, but is more concerned with the reaction of whole systems or individual actors in a system to a changing environment.
An important aim of this seminar is to combine research from concurrent systems with results from the adaptive systems community in order to develop formalisms for specifying collective adaptive systems, to increase the scalability of qualitative and quantitative modelling and analysis techniques to large systems, and to apply them to systems that dynamically change their structure or adapt to novel situations.

The seminar will focus on the following topics:

Process calculi, types and logics for collective adaptive systems
Modelling techniques and languages for collective adaptive systems based on the above formalisms
Quantitative and qualitative analysis techniques for collective adaptive systems.
The seminar will feature talks by the participants, interleaved with working groups in areas such as "Modelling and analysing systems which change at run time" and "Scaling qualitative and quantitative modelling and analysis methods". The last day will be reserved for the presentation of the results of the working groups, joint discussion, and planning of future joint activities between the participants. To disseminate the results of the seminar, we plan to edit a special issue in a suitable journal.

• Modelling / Simulation
• Semantics / Formal Methods
  • of
    • Qualitative and quantitative reasoning
    • Autonomic and adaptive systems
    • Swarm computing
    • Self-awareness
    • Formal methods