Challenges for Quantitative Analysis of Collective Adaptive Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8358)


We are surrounded by both natural and engineered collective systems. Such systems include many entities, which interact locally and, without necessarily having any global knowledge, nevertheless work together to create a system with discernible characteristics at the global level; a phenomenon sometimes termed emergence. Examples include swarms of bees, flocks of birds, spread of disease through a population, traffic jams and robot swarms. Many of these systems are also adaptive in the sense that the constituent entities can respond to their perception of the current state of the system at large, changing their behaviour accordingly.


Collective Adaptive Systems (CAS) Robot Swarm Stochastic Process Algebras (SPA) Continuous-time Markov Chain (CTMC) Fluid Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is partially supported by the EU project QUANTICOL, 600708.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.LFCS, School of InformaticsUniversity of EdinburghScotlandUK

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