Engineering Self-organising Systems with the Multi-Agent Paradigm

Last modified by Andrea Omicini on 16/06/2021 22:00

Luca Gardelli

Self-organisation is increasingly being regarded as an effective approach to tackle modern systems complexity. The self-organisation approach allows the develop- ment of systems exhibiting complex dynamics and adapting to environmental perturbations without requiring a complete knowledge of the future surrounding conditions. However, the development of self-organising systems (SOS) is driven by dif- ferent principles with respect to traditional software engineering. For instance, engineers typically design systems combining smaller elements where the compo- sition rules depend on the reference paradigm, but typically produce predictable results. Conversely, SOS display non-linear dynamics, which can hardly be cap- tured by deterministic models, and, although robust with respect to external perturbations, are quite sensitive to changes on inner working parameters. In this thesis, we describe methodological aspects concerning the early-design stage of SOS built relying on the Multiagent paradigm: in particular, we refer to the A&A metamodel, where MAS are composed by agents and artefacts, i.e. environmental resources. Then, we describe an architectural pattern that has been extracted from a recurrent solution in designing self-organising systems: this pattern is based on a MAS environment formed by artefacts, modelling non-proactive resources, and environmental agents acting on artefacts so as to enable self-organising mechanisms. In this context, we propose a scientific ap- proach for the early design stage of the engineering of self-organising systems: the process is an iterative one and each cycle is articulated in four stages, mod- elling, simulation, formal verification, and tuning. During the modelling phase we mainly rely on the existence of a self-organising strategy observed in Nature and, hopefully encoded as a design pattern. Simulations of an abstract sys- tem model are used to drive design choices until the required quality properties are obtained, thus providing guarantees that the subsequent design steps would lead to a correct implementation. However, system analysis exclusively based on simulation results does not provide sound guarantees for the engineering of complex systems: to this purpose, we envision the application of formal verifica- tion techniques, specifically model checking, in order to exactly characterise the system behaviours. During the tuning stage parameters are tweaked in order to meet the target global dynamics and feasibility constraints. In order to evaluate the methodology, we analysed several systems: in this thesis, we only describe three of them, i.e. the most representative ones for each of the three years of PhD course. We analyse each case study using the presented method, and describe the exploited formal tools and techniques.

Thesis Data

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