Towards Hybrid and Diversity-Aware Collective Adaptive Systems
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Towards Hybrid and Diversity-Aware Collective Adaptive Systems

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by Fausto Giunchiglia, Vincenzo Maltese, Stuart Anderson & Daniele Miorandi. Presentation given by Stuart Anderson at the Focas workshop @ ECAL 2013.

by Fausto Giunchiglia, Vincenzo Maltese, Stuart Anderson & Daniele Miorandi. Presentation given by Stuart Anderson at the Focas workshop @ ECAL 2013.

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Towards Hybrid and Diversity-Aware Collective Adaptive Systems Towards Hybrid and Diversity-Aware Collective Adaptive Systems Presentation Transcript

  • Fausto Giunchiglia Vincenzo Maltese Stuart Anderson Daniele Miorandi DISI, University of Trento, Trento, Italy School of Informatics, University of Edinburgh, Edinburgh, UK U-Hopper & CREATE-NET, Trento, Italy Towards Hybrid and Diversity-Aware Collective Adaptive Systems 18/09/2013 www.smart-society-project.eu
  • Smart Society 18/09/2013 www.smart-society-project.eu 2
  • Ride sharing application 18/09/2013 www.smart-society-project.eu 3
  • 18/09/2013 www.smart-society-project.eu 4
  • How is this Collective Adaptive? 18/09/2013 www.smart-society-project.eu 5  Reputation (Joe should have one too)  Reputation is a collective asset.  Reputation drives selection process  Reputation aggregates behaviour
  • Aggregation/Stratification 18/09/2013 www.smart-society-project.eu 6  Aggregation builds collective assets.  Goes together with stratification  Stratification determines the “relevant” population  Stratification is driven by particular observations on the population.  Aggregation/Stratification builds layered systems  Aggregation/Stratification support collectives as actors  Empirically there are ethical concerns  Aggregation used to justify lack of transparency  Stratification can identify
  • Layered Systems 18/09/2013 www.smart-society-project.eu 7  Layer 2: Incentivising the creation of self organising transport groups – analyse data, bring people together, improved reliability, stable cost.  Aggregation of Trip data is essential to achieve this and stratification drives specificity.  The extra layer changes evidence from the first layer.  Layer 3: Incentivise the creation of policy experimentation based on evidence from layer 1 and 2.  Requires aggregation of modes of organisation/provision…
  • Social Computation 18/09/2013 www.smart-society-project.eu 8  Programming model that taking humans and programs working in close cooperation.  Human computation depends on resources (e.g. communication) and incentives  There are many emerging models:  Mechanical turk  Games with a purpose  Crowdsourcing  …
  • Compositionality 18/09/2013 www.smart-society-project.eu 9  Slogan – “the meaning of the whole is a function of the meaning of the parts”.  Key property if systems are to be intellectually tractable.  Many components don’t compose nicely.  Meaning is context dependent, “good enough” semantics could deploy humans to resolve context/calculate semantics, could be relativised to the context.  Compositionality potentially generalises ideas about aggregation suggests architectures of “social machines”
  • Conclusions 18/09/2013 www.smart-society-project.eu 10  Social computation is the key to support Hybridity.  Compositionality is the key tool to support Diversity and tractability of Social Computation.