Electronic Social Capital for Self-Organising Multi-Agent Systems

Abstract

It is a recurring requirement in open systems, such as networks, distributed systems, and socio-technical systems, that a group of agents must coordinate their behaviour for the common good. In those systems—where agents are heterogeneous—unexpected behaviour can occur due to errors or malice. Agents whose practices free-ride the system can be accepted to a certain level; however, not only do they put the stability of the system at risk, but they also compromise the agents that behave according to the system’s rules. In social systems, it has been observed that social capital is an attribute of individuals that enhances their ability to solve collective action problems. Sociologists have studied collective action through human societies and observed that social capital plays an important role in maintaining communities though time as well as in simplifying the decision-making in them. In this work, we explore the use of Electronic Social Capital for optimising self-organised collective action. We developed a context-independent Electronic Social Capital framework to test this hypothesis. The framework comprises a set of handlers that capture events from the system and update three different forms of social capital: trustworthiness, networks, and institutions. Later, a set of metrics are generated by the forms of social capital and used for decision-making. The framework was tested in different scenarios such as two-player games, n -player games, and public goods games. The experimental results show that social capital optimises the outcomes (in terms of long-term satisfaction and utility), reduces the complexity of decision-making, and scales with the size of the population. This work proposes an alternative solution using Electronic Social Capital to represent and reason with qualitative, instead of traditional quantitative, values. This solution could be embedded into socio-technical systems to incentivise collective action without commodifying the resources or actions in the system.