Can Social Agents Efficiently Perform in Automated Negotiation?

In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in the negotiation. We argue that, while optimizing one’s utility function is essential, agents in a society should not ignore the opponent’s utility in the final agreement to improve the agent’s long-term perspectives in the system. This article aims to show whether it is possible to design a social agent (i.e., one that aims to optimize both sides’ utility functions) while performing efficiently in an agent society. Accordingly, we propose a social agent supported by a portfolio of strategies, a novel tit-for-tat concession mechanism, and a frequency-based opponent modeling mechanism capable of adapting its behavior according to the opponent’s behavior and the state of the negotiation. The results show that the proposed social agent not only maximizes social metrics such as the distance to the Nash bargaining point or the Kalai point but also is shown to be a pure and mixed equilibrium strategy in some realistic agent societies.

Evaluation of Congestion Aware Social Metrics for Centrality-Based Routing

Opportunistic networks utilize pocket switching for routing where each node forwards its messages to a suitable next node. The selection of the forwarder node is crucial for the efficient performance of a routing protocol. In any opportunistic network, some nodes have a paramount role in the routing process and these nodes could be identified with the assistance of the existing centrality measures available in network theory. However, the central nodes tend to suffer from congestion because a large number of nodes that are relatively less central attempt to forward their payload to the central nodes to increase the probability of the message delivery. This paper evaluates mechanisms to transform the social encounters into congestion aware metrics so that high-ranking central nodes are downgraded when they encounter congestion. The network transformations are aimed at aggregating the connectivity patterns of the nodes to implicitly accumulate the network information to be utilized by centrality measures for routing purposes. We have analyzed the performance of the metrics’ computed centrality measures using routing simulation on three real-world network traces. The results revealed that betweenness centrality along with the congestion aware network metrics holds the potential to deliver a competitive number of messages. Additionally, the proposed congestion aware metrics significantly balance the routing load among the central nodes.

Determining and systematizing metrics of the economic growth potential of rural areas: Considerations of the specifics of the international approach

Subject. The article discusses key indicators of the economic growth potential of rural areas with respect to the specifics of the international approach. Objectives. We study approaches to determining the concept of economic growth and key concepts of rural area development, which prevail in modern economics. The study also analyzes the applicable sets of indicators contributing to the effective evaluation and stimulation of the economic growth potential of rural areas. Methods. The study is based on the analysis of the existing theories of the economic growth in rural areas. We systematized economic knowledge and practices of determining economic growth indicators. Results. We analyzed basic difficulties in determining key economic growth drivers in rural areas, and identified aspects that influence the sustainable development and transformation of rural areas, referring to the use of innovative development concepts and their competitive advantages. The article sorts out key groups of various social metrics of the economic growth potential, and shows various combinations of socio-economic development indicators of rural areas. Conclusions and Relevance. The economic growth of rural areas depends in opportunities and drivers of effective strategic development, for which the growth potential should be adequately assessed and implemented. Evaluating the economic growth potential and development of rural areas, it is possible to set up crucial goals for raising the efficiency and competitiveness, such as the development of modern agricultural production, the establishment of the balanced administrative system and the creation of reasons for the State, business and people to follow common interests in order to improve the quality of rural life.

Opportunistic Network Algorithms for Internet Traffic Offloading in Music Festival Scenarios

Constant Internet connectivity has become a necessity in our lives. Hence, music festival organizers allocate part of their budget for temporary Wi-Fi equipment in order to sustain the high network traffic generated in such a small geographical area, but this naturally leads to high costs that need to be decreased. Thus, in this paper, we propose a solution that can help offload some of that traffic to an opportunistic network created with the attendees’ smartphones, therefore minimizing the costs of the temporary network infrastructure. Using a music festival-based mobility model that we propose and analyze, we introduce two routing algorithms which can enable end-to-end message delivery between participants. The key factors for high performance are social metrics and limiting the number of message copies at any given time. We show that the proposed solutions are able to offer high delivery rates and low delivery delays for various scenarios at a music festival.

Well-Being in Industrialized Economies and the Case for Firms’ Investment in Employee Learning

The idea of enhancing the well-being of employees through employment and skills development has gained greater emphasis in economic growth strategies. This new performance lens challenges the primacy given to financial metrics over social metrics such as health and happiness and brings multiple stakeholder interests into play. This chapter examines the evidence base for employee learning as a pathway to well-being. The case is made for a renewed focus on employee learning enabling transformative change that supports individuals, organizations, and society.

COVID-19 and Overall Mortality Inequities in the Surge in Death Rates by Zip Code Characteristics: Massachusetts, January 1 to May 19, 2020

Objectives. To address evidence gaps in COVID-19 mortality inequities resulting from inadequate race/ethnicity data and no socioeconomic data. Methods. We analyzed age-standardized death rates in Massachusetts by weekly time intervals, comparing rates for January 1 to May 19, 2020, with the corresponding historical average for 2015 to 2019 stratified by zip code social metrics. Results. At the surge peak (week 16, April 15–21), mortality rate ratios (comparing 2020 vs 2015–2019) were 2.2 (95% confidence interval [CI] = 1.4, 3.5) and 2.7 (95% CI = 1.4, 5.5) for the lowest and highest zip code tabulation area (ZCTA) poverty categories, respectively, with the 2020 peak mortality rate 1.1 (95% CI = 1.0, 1.3) times higher in the highest than the lowest poverty ZCTA. Similarly, rate ratios were significantly elevated for the highest versus lowest quintiles with respect to household crowding (1.7; 95% CI = 1.0, 2.9), racialized economic segregation (3.1; 95% CI = 1.8, 5.3), and percentage population of color (1.8; 95% CI = 1.6, 2.0). Conclusions. The COVID-19 mortality surge exhibited large inequities. Public Health Implications. Using zip code social metrics can guide equity-oriented COVID-19 prevention and mitigation efforts.

Social Networks’ Engagement During the COVID-19 Pandemic in Spain: Health Media vs. Healthcare Professionals

An increased use of social networks is one of the most far-reaching consequences of the COVID-19 pandemic. Aside from the traditional media, as the main drivers of social communication in crisis situations, individual profiles have emerged supported by social networks, which have had a similar impact to the more specialized communication media. This is the hypothesis of the research presented, which is focused on health communication and based on a virtual ethnography methodology with the use of social metrics. The aim is to understand the relationship established between the population in general and digital media in particular through the measurement of engagement. In this regard, a comparative study was carried out that describes this phenomenon over a period of six months on three social networks: YouTube, Twitter and Instagram, with a sample composed of specialized health media versus healthcare professionals. The results point to a new communications model that opens up a new space for agents whose content has a degree of engagement comparable to and even exceeding that of digital media specialized in health communication. The conclusions show that the crisis of the pandemic has accelerated the transformation of the communication sector, creating new challenges for the communication industry, media professionals, and higher education institutions related to market demands.