Reasoning (on) service component ensembles in rewriting logic Programming autonomic systems with massive number of heterogeneous components poses a number of challenges to language designers and software engineers and requires the integration of computational tools and reasoning tools. We present a general methodology to enrich SCEL, a recently introduced language for programming systems with massive numbers of components, with reasoning capabilities that are guaranteed by external reasoners. We show how the methodology can be instantiated by considering the Maude implementation of SCEL and a specific reasoner, Pirlo, implemented in Maude as well. Moreover we show how the actual integration can benefit from the existing analytical tools of the Maude framework. In particular, we demonstrate our approach by considering a simple scenario consisting of a group of robots moving in an arena aiming at minimising the number of collisions.
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References in zbMATH (referenced in 3 articles )
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- Neubert, Stefanie; Belzner, Lenz; Wirsing, Martin: Algebraic reinforcement learning. Hypothesis induction for relational reinforcement learning using term generalization. (2015)
- Belzner, Lenz; De Nicola, Rocco; Vandin, Andrea; Wirsing, Martin: Reasoning (on) service component ensembles in rewriting logic (2014)
- De Nicola, Rocco; Lluch Lafuente, Alberto; Loreti, Michele; Morichetta, Andrea; Pugliese, Rosario; Senni, Valerio; Tiezzi, Francesco: Programming and verifying component ensembles (2014)