Socially-Sensitive Systems Design:Exploring Social Potential

In human society, individuals have long voluntarily organized themselves in groups, which embody, provide and/or facilitate a range of different social concepts, such as governance, justice, or mutual aid. These social groups vary in form, size, and permanence, but in different ways provide benefits to their members. In turn, members of these groups use their understanding and awareness of group expectations to help determine their own actions, to the benefit of themselves, each other, and the health of the group

Collective attention and active consumer participation in community energy systems

Community energy systems, which rely on demand-side self-organisation of energy distribution, can encounter situations in which demand exceeds supply, and unless the community members schedule energy usage by and between themselves, there will be a blackout. This is effectively a collective action dilemma typically modelled as a repeated game and analysed using Game Theory. In this paper, we investigate the situation from an empirical (rather than analytic) perspective using instead a Serious Game. Motivated firstly by Elinor Ostrom's institutional design principles for sustainable common-pool resource management, and secondly by the idea that collective attention is a prerequisite for successful collective action, we present the design and implementation of a Serious Game which both encapsulates (some of) the design principles and promotes collective attention within the game's interface, affordances and interactions. Our experimental results show that as more interface design features which promote collective attention are enabled, then more often successful collective action is observed. These results have, we argue, important implications for Smart Meter design and roll-out programmes, as well as leveraging the active participation of prosumers in innovative operational and management principles for future Smart Grids

Adaptation strategies for self-organising electronic institutions

For large-scale systems and networks embedded in highly dynamic, volatile, and unpredictable environments, self-adaptive and self-organising (SASO) algorithms have been proposed as solutions to the problems introduced by this dynamism, volatility, and unpredictability. In open systems it cannot be guaranteed that an adaptive mechanism that works well in isolation will work well — or at all — in combination with others. In complexity science the emergence of systemic, or macro-level, properties from individual, or micro-level, interactions is addressed through mathematical modelling and simulation. Intermediate meso-level structuration has been proposed as a method for controlling the macro-level system outcomes, through the study of how the application of certain policies, or norms, can affect adaptation and organisation at various levels of the system. In this context, this thesis describes the specification and implementation of an adaptive affective anticipatory agent model for the individual micro level, and a self-organising distributed institutional consensus algorithm for the group meso level. Situated in an intelligent transportation system, the agent model represents an adaptive decision-making system for safe driving, and the consensus algorithm allows the vehicles to self-organise agreement on values necessary for the maintenance of “platoons” of vehicles travelling down a motorway. Experiments were performed using each mechanism in isolation to demonstrate its effectiveness. A computational testbed has been built on a multi-agent simulator to examine the interaction between the two given adaptation mechanisms. Experiments involving various differing combinations of the mechanisms are performed, and the effect of these combinations on the macro-level system properties is measured. Both beneficial and pernicious interactions are observed; the experimental results are analysed in an attempt to understand these interactions. The analysis is performed through a formalism which enables the causes for the various interactions to be understood. The formalism takes into account the methods by which the SASO mechanisms are composed, at what level of the system they operate, on which parts of the system they operate, and how they interact with the population of the system. It is suggested that this formalism could serve as the starting point for an analytic method and experimental tools for a future systems theory of adaptation.Open Acces

Modelling enduring institutions: The complementarity of evolutionary and agent-based approaches

Empirical work has shown that societies can sometimes avoid antisocial outcomes , such as the Tragedy of the Commons, by establishing institutional rules that govern their interactions. Moreover, groups are more likely to avoid antisocial outcomes when they design and enforce their own rules. But this raises the question: when will group members put effort into maintaining their institution so that it continues to provide socially beneficial outcomes? Ostrom derived a set of empirical principles that predict when institutions will endure, which have subsequently been formalised in agent-based models that are based on an executable description of the content of an individual's behaviour. Here we show how these models can be complemented by evolutionary game theory, which focuses on the value or payoff of different behaviours, rather than on the mechanistic content of the behaviour. Using such a value-based model, we determine exactly when individuals will be incentivised to maintain their institution and enforce its rules, including the critical amount that a group must invest into incentivising agents to monitor rule compliance. We highlight the complementarity of content-based and value-based modelling approaches, and therefore provide a step towards unifying theoretical and empirical approaches to understanding enduring institutions and other social phenomena

Fostering cooperation through dynamic coalition formation and partner switching

In this article we tackle the problem of maximizing cooperation among self-interested agents in a resource exchange environment. Our main concern is the design of mechanisms for maximizing cooperation among self-interested agents in a way that their profits increase by exchanging or trading with resources. Although dynamic coalition formation and partner switching (rewiring) have been shown to promote the emergence and maintenance of cooperation for self-interested agents, no prior work in the literature has investigated whether merging both mechanisms exhibits positive synergies that lead to increase cooperation even further. Therefore, we introduce and analyze a novel dynamic coalition formation mechanism, that uses partner switching, to help self-interested agents to increase their profits in a resource exchange environment. Our experiments show the effectiveness of our mechanism at increasing the agents' profits, as well as the emergence of trading as the preferred behavior over different types of complex networks. © 2014 ACM.The first author thanks the grant Formación de Profesorado Universitario (FPU), reference AP2010-1742. J.Ll.A. and J.A.R-A are partially funded by projects EVE (TIN2009-14702-C02-01), AT (CSD2007-0022), COR (TIN2012-38876-C02-01), MECER (201250E053), and the Generalitat of Catalunya grant 2009-SGR-1434Peer Reviewe

Collective Adaptive Systems: Qualitative and Quantitative Modelling and Analysis (Dagstuhl Seminar 14512)

This report documents the program and the outcomes of Dagstuhl Seminar 14512 "Collective Adaptive Systems: Qualitative and Quantitative Modelling and Analysis". Besides presentations on current work in the area, the seminar focused on the following topics: (i) Modelling techniques and languages for collective adaptive systems based on the above formalisms. (ii) Verification of collective adaptive systems. (iii) Humans-in-the-loop in collective adaptive systems

Multi-agent based simulation of self-governing knowledge commons

The potential of user-generated sensor data for participatory sensing has motivated the formation of organisations focused on the exploitation of collected information and associated knowledge. Given the power and value of both the raw data and the derived knowledge, we advocate an open approach to data and intellectual-property rights. By treating user-generated content as well as derived information and knowledge as a common-pool resource, we hypothesise that all participants can be compensated fairly for their input. To test this hypothesis, we undertake an extensive review of experimental, commercial and social participatory-sensing applications, from which we identify that a decentralised, community-oriented governance model is required to support this open approach. We show that the Institutional Analysis and Design framework as introduced by Elinor Ostrom, in conjunction with a framework for self-organising electronic institutions, can be used to give both an architectural and algorithmic base for the necessary governance model, in terms of operational and collective choice rules specified in computational logic. As a basis for understanding the effect of governance on these applications, we develop a testbed which joins our logical formulation of the knowledge commons with a generic model of the participatory-sensing problem. This requires a multi-agent platform for the simulation of autonomous and dynamic agents, and a method of executing the logical calculus in which our electronic institution is specified. To this end, firstly, we develop a general purpose, high performance platform for multi-agent based simulation, Presage2. Secondly, we propose a method for translating event-calculus axioms into rules compatible with business rule engines, and provide an implementation for JBoss Drools along with a suite of modules for electronic institutions. Through our simulations we show that, when building electronic institutions for managing participatory sensing as a knowledge commons, proper enfranchisement of agents (as outlined in Ostrom's work) is key to striking a balance between endurance, fairness and reduction of greedy behaviour. We conclude with a set of guidelines for engineering knowledge commons for the next generation of participatory-sensing applications.Open Acces

Collisions, Design & The Swerve

If only everything were formed of neat laminar flows, with easy to understand conditions, and determinable outcomes: there would be no risk to manage out, messy inconsistencies and uncertainties to disrupt well-laid out plans. Things are not so clear-cut however. Indeed, as scientists, poets and philosophers of science have pointed out it is under conditions of nondeterminism and complexity that everything comes into being. There is an issue, then, when creative disciplines in particular find such complexity problematic enough to design systems and models in which uncertainty, disruption and aleatory collisions are if not destroyed, then dampened. We wonder: what might become of a creative practice that championed its encounter with The Swerve, Lucretius's clinamen? This article examines the role, value and applicability of the concept of collision to design. It takes a philosophical approach to examining this concept and mapping the possibilities of its use in design. We will argue using concepts mainly from Lucretius and Serres – but also Deleuze and others – that collision is an important aspect of all creativity, and that there would be nothing were it not for collisions, disruptive deviation and swerves from equilibrium. The aim will be to articulate the conditions for the possibility of designing that is a 'fan of collisions'