Community Currencies (CCs) in Spain: An empirical study of their social effects

Despite its sudden proliferation along the economic crisis period, no previous study has investigated the social effects of the community currency (CCs) experiences in Spain. Previous research on CCs experiences from different countries provided evidences about social capital improvement, introducing CCs as sustainability tools. This research uses the theoretical frameworks of social capital and complex adaptive systems to approach concepts like sustainability, networks, trust, norms, participation and cooperation. Statistical analysis of the data collected in June 2013 through online survey explores social capital and resilience indicators among the Spanish exchange community users, concluding that Spanish CCs systems improve community social capital through the proposed dimensions, although they are in an early stage and several weakness need to be corrected. The values, motivations, attitude and positive perception of their members suggest that CCs could be appropriate tools for sustainability due its potential to improve social capital and resilience. Detected weakness may affect the interests and commitment of their members. Therefore experience from senior currency systems may help them to face adversities and fully develop their potential for sustainability.Despite its sudden proliferation along the economic crisis period, no previous study has investigated the social effects of the community currency (CCs) experiences in Spain. Previous research on CCs experiences from different countries provided evidences about social capital improvement, introducing CCs as sustainability tools. This research uses the theoretical frameworks of social capital and complex adaptive systems to approach concepts like sustainability, networks, trust, norms, participation and cooperation. Statistical analysis of the data collected in June 2013 through online survey explores social capital and resilience indicators among the Spanish exchange community users, concluding that Spanish CCs systems improve community social capital through the proposed dimensions, although they are in an early stage and several weakness need to be corrected. The values, motivations, attitude and positive perception of their members suggest that CCs could be appropriate tools for sustainability due its potential to improve social capital and resilience. Detected weakness may affect the interests and commitment of their members. Therefore experience from senior currency systems may help them to face adversities and fully develop their potential for sustainability

A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems

Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functionalities of the systems mentioned above. The objective of this paper is to define a process algebraic framework for the modeling of systems that use (i) trust and reputation to govern the interactions among nodes, and (ii) communication models characterized by a high level of adaptiveness and flexibility. Hence, we propose a formalism for verifying, through model checking techniques, the robustness of these systems with respect to the typical attacks conducted against webs of trust.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

Trust Mining and analysis in complex systems

A complex system, as a collection of loosely coupled interacting components, can group and create functioning units together. Complex systems have become a powerful framework for describing, analysing, modelling systems in nature and society. Trust among components, established by considering past interactions, represents a subjective expectation which a component has about another’s future behaviour to perform given activities dependably, securely, and reliably. Hence, trust is essential to effectively reduce the perceived risks of transactions and guide future interactions. It is applied to quantify the performance of both individual component behaviours and the correlations among interdependent components in a complex system. With regard to certain challenges in the current complex system research, this thesis deeply investigates trust relationships among components within two different types of complex systems, i.e., the collaborative complex system and the preference system, and proposes three trust estimation approaches. Firstly, collaborative complex systems consist of loosely coupled autonomous and adaptive components. In order to address complicated problems which usually require multiple skills and functions, components are grouped as composite teams and collaborate by providing different knowledge, resource and skill. Two types of team formation strategies for collaborative complex systems are proposed for scenarios of team formation without predefined workflow structures, and team formation with predefined workflow structures, respectively. Hence, the Correlated Contribution trust evaluation model is proposed to explore the compositional trust through considering correlations and dependencies among both skills required by tasks and individual components within collaborative composite teams. Furthermore, we propose an automatic approach, i.e., the Same Edge Contribution trust evaluation model, to estimate the trustworthiness of proposed candidate composite teams by analysing historical provenance graphs which are adopted to capture pre- defined workflow structures. Finally, preference systems mainly focus on the entities with similar preferences and group them into various communities. However, in the real world, a particular entity usually places its trust differently from other social entities, because of their multi-faceted interests and preferences. In this thesis, a Community- Based trust estimation approach is proposed to explore the similarity of criteria or preference among entities within the same community in relation to a certain context. It automatically infers trust relationships among entities from previous entity-generated feedback, and predict a particular entity’s potential feedback for items which the entity does not have previous experience with

Verbal Explanations for Deep Reinforcement Learning Neural Networks with Attention on Extracted Features

In recent years, there has been increasing interest in transparency in Deep Neural Networks. Most of the works on transparency have been done for image classification. In this paper, we report on work of transparency in Deep Reinforcement Learning Networks (DRLNs). Such networks have been extremely successful in learning action control in Atari games. In this paper, we focus on generating verbal (natural language) descriptions and explanations of deep reinforcement learning policies. Successful generation of verbal explanations would allow better understanding by people (e.g., users, debuggers) of the inner workings of DRLNs which could ultimately increase trust in these systems. We present a generation model which consists of three parts: an encoder on feature extraction, an attention structure on selecting features from the output of the encoder, and a decoder on generating the explanation in natural language. Four variants of the attention structure full attention, global attention, adaptive attention and object attention - are designed and compared. The adaptive attention structure performs the best among all the variants, even though the object attention structure is given additional information on object locations. Additionally, our experiment results showed that the proposed encoder outperforms two baseline encoders (Resnet and VGG) on the capability of distinguishing the game state images

Acceptability of the e-authentication in higher education studies: views of students with special educational needs and disabilities

Trust-based e-assessment systems are increasingly important in the digital age for both academic institutions and students, including students with special educational needs and disabilities (SEND). Recent literature indicates a growing number of studies about e-authentication and authorship verification for quality assurance with more flexible modes of assessment. Yet understanding the acceptability of e-authentication systems among SEND students is underexplored. This study examines SEND students’ views about the use of e-authentication systems, including perceived advantages and disadvantages of new technology-enhanced assessment. This study aims to shed light on this area by examining the attitudes of 267 SEND students who used, or were aware of, an authentication system known as adaptive trust-based e-assessment system for learning (TeSLA). The results suggest a broadly positive acceptability of these e-authentication technologies by SEND students. In the view of these students, the key advantages are the ability of proving the originality of their work, and trust-based e-assessment results; the key disadvantages are the possibility that the technology might not work or present wrong outputs in terms of cheating

Cultivating Systems Leadership in Cross-Sector Partnerships: Lessons from the Linked Learning Regional Hubs of Excellence

Investments in the social sector have become increasingly complex, with many foundations shifting from supports for single organizations toward more systemic strategies focused on improving outcomes for entire communities. As a result, the field has become awash in regional, or place-based, investments that rely on cross-sector partnerships and networks to drive change. These efforts require coordination among stakeholders across all levels of the practice and policy continuum – from direct service providers, to nonprofit intermediaries, funders, advocacy organizations, and policymakers.It is in this context, and in the spirit of continuous learning, that The James Irvine Foundation's Linked Learning Regional Hubs of Excellence investment serves as a systems change experiment, offering insights and critical lessons that can inform others undertaking similar work. The aim of this Issue Brief – authored by Equal Measure and Harder+Company – is to contribute to field dialogue and learning about the role of leadership in complex systems change strategies, particularly those focused on producing equitable impacts in college and career readiness.Equal Measure and Harder+Company serve as the evaluators of The James Irvine Foundation's Linked Learning Regional Hubs of Excellence. They work in partnership with Jobs for the Future, the intermediary and technical assistance provider for this initiative

Potential benefits of an adaptive forward collision warning system

Forward collision warning (FCW) systems can reduce rear-end vehicle collisions. However, if the presentation of warnings is perceived as mistimed, trust in the system is diminished and drivers become less likely to respond appropriately. In this driving simulator investigation, 45 drivers experienced two FCW systems: a non-adaptive and an adaptive FCW that adjusted the timing of its alarms according to each individual driver’s reaction time. Whilst all drivers benefited in terms of improved safety from both FCW systems, non-aggressive drivers (low sensation seeking, long followers) did not display a preference to the adaptive FCW over its non-adaptive equivalent. Furthermore, there was little evidence to suggest that the non-aggressive drivers’ performance differed with either system. Benefits of the adaptive system were demonstrated for aggressive drivers (high sensation seeking, short followers). Even though both systems reduced their likelihood of a crash to a similar extent, the aggressive drivers rated each FCW more poorly than their non-aggressive contemporaries. However, this group, with their greater risk of involvement in rear-end collisions, reported a preference for the adaptive system as they found it less irritating and stress-inducing. Achieving greater acceptance and hence likely use of a real system is fundamental to good quality FCW design

Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges

Human-swarm interaction (HSI) involves a number of human factors impacting human behaviour throughout the interaction. As the technologies used within HSI advance, it is more tempting to increase the level of swarm autonomy within the interaction to reduce the workload on humans. Yet, the prospective negative effects of high levels of autonomy on human situational awareness can hinder this process. Flexible autonomy aims at trading-off these effects by changing the level of autonomy within the interaction when required; with mixed-initiatives combining human preferences and automation's recommendations to select an appropriate level of autonomy at a certain point of time. However, the effective implementation of mixed-initiative systems raises fundamental questions on how to combine human preferences and automation recommendations, how to realise the selected level of autonomy, and what the future impacts on the cognitive states of a human are. We explore open challenges that hamper the process of developing effective flexible autonomy. We then highlight the potential benefits of using system modelling techniques in HSI by illustrating how they provide HSI designers with an opportunity to evaluate different strategies for assessing the state of the mission and for adapting the level of autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling Conference, Canberra, Australi

Domino: exploring mobile collaborative software adaptation

Social Proximity Applications (SPAs) are a promising new area for ubicomp software that exploits the everyday changes in the proximity of mobile users. While a number of applications facilitate simple file sharing between co–present users, this paper explores opportunities for recommending and sharing software between users. We describe an architecture that allows the recommendation of new system components from systems with similar histories of use. Software components and usage histories are exchanged between mobile users who are in proximity with each other. We apply this architecture in a mobile strategy game in which players adapt and upgrade their game using components from other players, progressing through the game through sharing tools and history. More broadly, we discuss the general application of this technique as well as the security and privacy challenges to such an approach