@article{eprints1536,
          author = {Roberto Bruni and Andrea Corradini and Fabio Gadducci and Alberto Lluch-Lafuente and Andrea Vandin},
           title = {Modelling and analyzing adaptive self-assembling strategies with Maude},
       publisher = {Elsevier},
         journal = {Science of Computer Programming},
        abstract = {Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA.},
             url = {http://eprints.imtlucca.it/1536/}
}