Conformity-Driven Agents Support Ordered Phases in the Spatial Public Goods Game

We investigate the spatial Public Goods Game in the presence of fitness-driven and conformity-driven agents. This framework usually considers only the former type of agents, i.e., agents that tend to imitate the strategy of their fittest neighbors. However, whenever we study social systems, the evolution of a population might be affected also by social behaviors as conformism, stubbornness, altruism, and selfishness. Although the term evolution can assume different meanings depending on the considered domain, here it corresponds to the set of processes that lead a system towards an equilibrium or a steady-state. We map fitness to the agents' payoff so that richer agents are those most imitated by fitness-driven agents, while conformity-driven agents tend to imitate the strategy assumed by the majority of their neighbors. Numerical simulations aim to identify the nature of the transition, on varying the amount of the relative density of conformity-driven agents in the population, and to study the nature of related equilibria. Remarkably, we find that conformism generally fosters ordered cooperative phases and may also lead to bistable behaviors.Comment: 13 pages, 5 figure

Degree Correlations in Random Geometric Graphs

Spatially embedded networks are important in several disciplines. The prototypical spatial net- work we assume is the Random Geometric Graph of which many properties are known. Here we present new results for the two-point degree correlation function in terms of the clustering coefficient of the graphs for two-dimensional space in particular, with extensions to arbitrary finite dimension

Coevolution of Synchronization and Cooperation in Costly Networked Interactions

Despite the large number of studies on synchronization, the hypothesis that interactions bear a cost for involved individuals has seldom been considered. The introduction of costly interactions leads, instead, to the formulation of a dichotomous scenario in which an individual may decide to cooperate and pay the cost in order to get synchronized with the rest of the population. Alternatively, the same individual can decide to free ride, without incurring any cost, waiting for others to get synchronized to his or her state. Thus, the emergence of synchronization may be seen as the byproduct of an evolutionary game in which individuals decide their behavior according to the benefit-to-cost ratio they accrued in the past. We study the onset of cooperation and synchronization in networked populations of Kuramoto oscillators and report how topology is essential in order for cooperation to thrive. We also display how different classes of topology foster synchronization differently both at microscopic and macroscopic levels

Computational behavioral models in public goods games with migration between groups

In this study we have simulated numerically two models of linear public goods games where players are equally distributed among a given number of groups. Agents play in their group by using two simple sets of rules, called ‘blind’ and ‘rational’ model, respectively, that are inspired by the observed behavior of human participants in laboratory experiments. In addition, unsatisfied agents have the option of leaving their group and migrating to a new random one through probabilistic choices. Stochasticity, and the introduction of two types of players in the blind model, help simulate the heterogeneous behavior that is often observed in experimental work. Our numerical simulations of the corresponding dynamical systems show that being able to leave a group when unsatisfied favors contribution and avoids free-riding to a good extent in a range of the enhancement factor where defection would prevail without migration. Our numerical simulation presents results that are qualitatively in line with known experimental data when human agents are given the same kind of information about themselves and the other players in the group. This is usually not the case with customary mathematical models based on replicator dynamics or stochastic approaches. As a consequence, models like the ones described here may be useful for understanding experimental results and also for designing new experiments by first running cheap computational simulations instead of doing costly preliminary laboratory work. The downside is that models and their simulation tend to be less general than standard mathematical approaches.A A acknowledges the financial support of the Spanish Ministry of Science and Innovation under the Grant No. IJC2019-040967-I

A Methodology for the Evaluation of the Voc Abatement Capacity of Different Species of Potted Ornamental Plants in Phytoremediating Indoor Air

Since the end of the ’80s, it has been known that potted ornamental plants can remediate Volatile Organic Compounds (VOCs) from indoor air and, to date, a significant number of species have been tested in controlled environments to quantify their abatement capacity concerning specific VOCs. However, the experimental methodologies are not standardised yet, and different units and approaches are used to quantify the removal capacity of the species. Consequently, in most cases, the results obtained are not comparable and, most importantly, directly exploitable to set up phytoremediation interventions in real settings. This study proposes a new method for evaluating and comparing the VOC removal capacity of different plant species and a review, produced according to this methodology, of the results obtained in previous studies. Considering that the VOC abatement is related to the entire plant system and that the uptake cannot be considered neither a zero nor a first-order removal process but a hybrid of the two, the proposal consists in modelling the removal analogously to biological processes. In the first instance, this approach allows a simple but effective assessment of the results obtained in different tests, making possible an objective choice of the best performing species for phytoremediation applications in real settings. While applying this methodology to existing experimental studies, it was considered essential to rigorously review their protocols as the removal depends on many factors, inter alia the chamber dimensions, the environmental conditions, the initial pollutant concentrations and the metabolic characteristics of the tested species. This application has aimed to set the basis for an accurate and more complete comparison of the results obtained in controlled environment experimentations and, also, to prepare the way to a standardization of the methodologies. Plant-based remediation interventions could be a simple, green and innovative solution to address the complex indoor air pollution problem. The approach proposed in this paper is an essential step towards a rational design of these interventions, allowing, in particular, the assessment of the actual remediation capacity of different plant species tested in various conditions

The Integration of Social Media Data in Emergency Management: an Innovative Decision Support System

The upsurge of social media platforms has opened to the prospect of integrating the information provided by citizens through these channels into the traditional emergency management process. This paper presents the Civil Protection Emergency System model designed for the Italo-Croatian decision support system developed in the Interreg project E-CITIJENS. Seismic, flood and forest fire are the risk typologies addressed. The model specifies the key steps that allow the system, a semantically enriched web-enabled platform, to identify and analyse significant social media posts that can provide Civil Protection authorities with additional real-time data regarding potential or ongoing emergencies in a designated geographical area. The approach chosen is to retrieve from social media the posts containing specific terms used by citizens during emergencies (i.e. an initial project terminology was developed) and to classify them according to their relative importance compared to the other posts selected, identifying those to be evaluated first by the Civil Protection staff. This is achieved by calculating the total score of each post as the sum of the scores attributed to the initial terminology keywords therein contained (i.e. three severity scales were defined to rank the terms according to their potential hazard level). This novel Civil Protection Emergency System model has been applied to a set of simulated emergency events with the aim of testing the algorithm and to verify the effectiveness of the platform in order to assess if it could provide helpful additional information to Civil Protection, improving its overall emergency coping capacity