Abstract
Open systems typically occur in a wide range of applications, from virtual organisations and vehicular networks to cloud/grid computing and reconfigurable manufacturing. All these applications encounter a similar problem: how does a system component reliably complete its own tasks, when successful task completion depends on interaction and interoperation with other, potentially unreliable and conflicting, components. One solution to this problem is trust: depending on a second party requires a willingness to expose oneself to risk, and to the extent that this ‘willingness’ can be quantified or qualified, it can be used to inform a binary trust decision. Therefore, a formal model of the social relationship underpinning such trust decisions is essential for conditioning bipartite interactions between components in an open system. However, there are a number of issues that follow from this – for example: what is to be done when the outcome of the trust decision is contrary to expectation? Are there positive externalities that can be derived from a successful trust decision? and: How can we ensure that outcomes of collective decision-making in such circumstances are, in some sense, ‘correct’ and/or ‘fair’. Our answers to these question have been found in the formalisation of other social relations, respectively forgiveness, social capital and justice. This chapter presents a survey of the development of formal models of social relations, from trust to justice via forgiveness and social capital, all of which address the issue of reliable interoperation in open systems.
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Notes
- 1.
Note this is different from open systems as defined from a systems theory perspective, i.e. a system which has interactions with its environment through some boundary; and from a computing perspective, where open systems are also defined as systems based on interoperability through open standards, or dynamic systems with unrestricted access and components that join and leave the system – although the open systems in which we are interested can exhibit all these features.
- 2.
The term ‘sociologically-inspired’ was chosen as a parallel to ‘biologically-inspired’, although it is not, perhaps, such a good term. We take inspiration not just from sociology, but from across the social and natural sciences, and indeed have formalised theories from linguistics, philosophy, law, psychology, cognitive science, physiology, economics, and political science in our search for computable solutions to engineering problems.
- 3.
Although Weisberg’s key, and highly cogent, point, is that in the pursuit of the elimination of doubt by data analytics and machine learning, some researchers appear to have neglected ambiguity and choose to remain wilfully ignorant of this component of uncertainty.
- 4.
It has been pointed out that previously broken bones also ache in stressful situations, such as cold weather – a reminder of the break. This may be stretching the analogy, but forgiving and somehow not quite forgetting, so that caution could be exercised in important situations, could be a beneficial feature of a future forgiveness framework.
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Acknowledgements
The work reported in this chapter is the product of numerous collaborations dating back more than ten years. Much of work on open systems in general and agent societies has been done with Alexander Artikis, and the methodology reported in Sect. 7.2 is joint work with Andrew Jones and Alexander Artikis. The work on the computational trust framework is joint with Brendan Neville; the work on the computational forgiveness framework is joint with Mina Vasalou; and the work on the computational social capital framework is joint with Patricio Petruzzi. The research programme on computational justice was initiated with Dídac Busquets and Régis Riveret. Needless to say, I am duly grateful for these valuable collaborations.
This chapter has benefitted greatly from the careful reading and the very helpful comments of the three anonymous reviewers, and many thanks for these encouraging remarks. The editors have been correspondingly helpful in the preparation and production of this chapter, for which again many thanks.
The work reported here has been supported by a number of European and UK projects, including ALFEBIITE (EU FET IST-1999-10298), HUMAiNE (EU NoE IST-2002-507422), Marie Curie Intra-European Fellowships ITS4SIT (FP7 274057) and NORMS4SRA (FP7 331472), and APS (EPSRC Autonomic Power System Grand Challenge I031650).
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Pitt, J. (2016). From Trust and Forgiveness to Social Capital and Justice: Formal Models of Social Processes in Open Distributed Systems. In: Reif, W., et al. Trustworthy Open Self-Organising Systems. Autonomic Systems. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-29201-4_7
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