Search

The topic of flood phenomena has always been of considerable importance due to the high risks it entails, both in terms of potential economic and social damage and the jeopardizing of human lives themselves. The spread of climate change is making this topic even more relevant. This work aims to contribute to evaluating the role that human factors can play in responding to critical hydrogeological phenomena. In particular, we introduce an agent-based platform for analyzing social behaviors in these critical situations. In our experiments, we simulate a population that is faced with the risk of a potentially catastrophic event. In this scenario, citizens (modeled through cognitive agents) must assess the risk they face by relying on their sources of information and mutual trust, enabling them to respond effectively. Specifically, our contributions include (1) an analysis of some behavioral profiles of citizens and authorities; (2) the identification of the "dissonance between evaluation and action" effect, wherein an individual may behave differently from what their information sources suggest, despite having full trust in them in situations of particular risk; (3) the possibility of using the social structure as a "social risk absorber", enabling support for a higher level of risk. While the results obtained at this level of abstraction are not exhaustive, they identify phenomena that can occur in real-world scenarios and can be useful in defining general guidelines. [ABSTRACT FROM AUTHOR]

Smart devices have a significant presence in our life. Humans and artificial entities are continuously interfacing across a variety of scenarios such as smart transportation, smart healthcare, smart grid, smart city, etc. Nevertheless, there are still different critical points to be faced. Among the many, given the ever-growing potential for action, a major issue concerns the autonomy of these devices. We propose a possible solution on how IoT devices may act to get more autonomy, in relation to the specific user they interface with. Thus, we considered a possible implementation in a simulation context, showing how the proposed approach works. [ABSTRACT FROM AUTHOR]

In a world where the interconnection and interaction between human and artificial agents are continuously increasing, the dynamics of social bonds and dependence networks play a fundamental role. The core of our investigation revolves around the intricate interplay between dependence and trust within a hybrid society, populated by human and artificial agents. By means of a structural theory, this study offers valuable insights into the utilization of dependence networks and their impact on collaborative dynamics and resource management. Most notably, agents that leverage dependence, even at the cost of interacting with low-trustworthiness partners, achieve superior performance in resource-constrained environments. On the other hand, in contexts where the use of dependence is limited, the role of trust is emphasized. These findings underscore the significance of dependence networks and their practical implications in real-world contexts, offering useful practical implications in areas such as robotics, resource management, and collaboration among human and artificial agents. [ABSTRACT FROM AUTHOR]

Italy was the first European state affected by COVID-19. Despite many uncertainties, citizens chose to trust the authorities and their trust was pivotal. This research aims to investigate the contribution of Italian citizens' trust in Public Institutions and how it influenced the acceptance of the necessary counter measures. Applying linear regression to a dataset of 4260 Italian respondents, we modelled trust from its main cognitive components, with particular reference to competence and willingness. Therefore, exploiting agent-based modelling, we investigated how these components affected trust and how trust evolution influences the acceptance of these restrictive measures. Our analysis confirms the key role of competence and willingness as cognitive components of trust. Results also suggest that a generic attempt to raise the average trust, besides being challenging, may not be the best strategy to increase compliance. Furthermore, reasoning at category level is a fundamental to identify the best components on which to invest. [ABSTRACT FROM AUTHOR]

Trust in vaccines and in the institutions responsible for their management is a key asset in the global response to the COVID-19 pandemic. By means of a structured multi-scales survey based on the socio-cognitive model of trust, this study investigates the interplay of institutional trust, confidence in COVID-19 vaccines, information habits, personal motivations, and background beliefs on the pandemic in determining willingness to vaccinate in a sample of Italian respondents (N = 4096). We observe substantial trust in public institutions and a strong vaccination intention. Theory-driven structural equation analysis revealed what factors act as important predictors of willingness to vaccinate: trust in vaccine manufacturers (which in turn is supported by trust in regulators), collectivist goals, self-perceived knowledgeability, reliance on traditional media for information gathering, and trust in institutional and scientific sources. In contrast, vaccine hesitancy, while confined to a minority, is more prominent in less educated and less affluent respondents. These findings can inform institutional decisions on vaccine communication and vaccination campaigns. [ABSTRACT FROM AUTHOR]

Trust has been clearly identified as a key concept for human–machine interaction (HMI): on the one hand, users should trust artificial systems; on the other hand, devices must be able to estimate both how much other agents trust them and how trustworthy the other agents are. Indeed, the applications of trust in these scenarios are so complex that often, the interaction models consider only a part of the possible interactions and not the system in its entirety. On the contrary, in this work, we made the effort to consider the different types of interaction together, showing the advantages of this approach and the problems it allows to face. After the theoretical formalization, we introduce an agent simulation to show the functioning of the proposed model. The results of this work provide interesting insights for the evolution of HMI models. [ABSTRACT FROM AUTHOR]

A great deal of effort has been made to introduce trust models to assess trustworthiness within virtual societies. The great majority of them makes extensive use of direct experience as the main source of information, considering recommendation/reputation and inferential processes just later, as a secondary mechanism to refine trust assessment. In this kind of networks, unfortunately, direct experience might not always represent the best solution to assess trustworthiness. In fact, their highly dynamic structure promotes an increase of the average number of interconnections among agents. This in turn negatively affects the degree of knowledge the agents possess about each specific individual, i.e. direct experience. To date, however, it has not been said much about how to face these situations. It is fundamental to find an effective approach for trust assessment even in lack of direct experience, which is the central focus of this research. By the means of a multi-agent social simulation, we consider the situation in which an agent can just access indirect knowledge for trust assessment, namely recommendations of specific individuals or whole categories of individuals. Then, we compare the efficiency of these two approaches in order to identify when it is more convenient to rely on the first or on the second one. As expected, our results confirm that the dynamic nature of these networks strongly affects the role of categories. We modeled this feature introducing the "turnover" in the simulations, whereby the higher is the turnover the more convenient it is relying on categories. Besides this confirmatory result, our simulations highlight the higher degree of robustness of categories in the presence of unreliable recommenders. Such a result is even more significant if there is no available information about how reliable the recommenders are. The results we obtained are in accordance with the current literature and can be of important interest for the development of this sector. [ABSTRACT FROM AUTHOR]

The central focus of this research is the fast and crucial impact of the COVID-19 pandemic on a crucial psychological, relational, and political construct: trust. We investigate how the consequences of the pandemic, in terms of healthcare, state intervention and impositions, and daily life and habits, have affected trust in public institutions in Italy, at the time when the contagion was rapidly spreading in the country (early March 2020). In this survey, addressed to 4260 Italian citizens, we analyzed and measured such impact, focusing on various aspects of trust. This attention to multiple dimensions of trust constitutes the key conceptual advantage of this research, since trust is a complex and layered construct, with its own internal dynamics. In particular, the analysis focuses on how citizens attribute trust to Public Authorities, in relation to the management of the health crisis: with regard to the measures and guidelines adopted, the purposes pursued, the motivations that determine them, their capacity for involvement, and their effectiveness for the containment of the virus itself. A pandemic creates a bilateral need for trust, both in Public Authorities (they have to rely on citizens' compliance and must try to promote and maintain their trust in order to be effective) and in citizens, since they need to feel that somebody can do something, can (has the power to) protect them, to act at the needed collective level. We are interested to explore how this need for trust affects the attributional process, regarding both attitudes and the corresponding decisions and actions. The most striking result of this survey is the very high level of institutional trust expressed by respondents: 75% of them trust Italian public authorities to be able to deal with the COVID-19 emergency. This is in sharp contrast with the relatively low levels of institutional trust characteristic of Italy, both historically and in recent surveys. Moreover, the survey allowed the discrimination of several potential predictors for trust, thus emphasizing factors that, during this crisis, are exhibiting an anomalous impact on trust. [ABSTRACT FROM AUTHOR]

The success of IoT technologies is undeniable. They are entering more and more in our lives, carrying out increasingly complex tasks. However, there are still a few problems we need to face and solve. For instance, it is not given that the users will be prepared to afford all the automation that IoT devices will offer or that it will be compatible with the users' cognitive attitudes and its actual and real goals. Within this work, we start analyzing which reasons undermine the acceptance of IoT systems and then we propose a possible solution, tanking into account not just the user-device interaction, but also how this affects the device-device interaction. Since the complexity of the tasks the user asks may require the cooperation of some devices to be realized, the regulation of this relationship represents a necessary step for this technology. The first contribution of this work is the level characterization of the autonomy a user can grant to an IoT device. The second contribution is a theoretical model to deal with users and to stimulate users' acceptance, taking also into account a possible, collaborative organizational structure, to manage the creation of groups and the partners' selection process. [ABSTRACT FROM AUTHOR]

In the next future the IoT system will introduce extraordinary changes in our daily life. We will communicate with our domestic appliances to inform them about our preferences and goals and they will develop initiative and autonomy to be put at our service. But are we sure that we can afford all the automation they could offer? Are we able to manage it? Is it compatible with our cognitive attitudes and our actual and real goals? In this paper, we face the question of the IoT from the point of view of the user. We start analyzing which reasons undermine the acceptance of IoT systems and then we propose a possible solution. The first contribution of this work is the level characterization of the autonomy a user can grant to an IoT device. The second contribution is a theoretical model to deal with users and to stimulate users' acceptance. By the means of simulation, we show how the model works and we prove that it leads the system to an optimal solution. [ABSTRACT FROM AUTHOR]

In this article, we are interested in the fact that relevance and trustworthiness of information acquired by an agent X from a source F strictly depends and derives from X's trust in F with respect to the kind of information. In particular, we are interested in analyzing the relevance of F's category as indicator for its trustworthiness with respect to the specific informative goals of X. In this article, we analyze an interactive cognitive model for searching information in a world in which each agent can be considered as belonging to a specific agent's category. We also consider variability within the canonical categorical behavior and consequent influence on the trustworthiness of provided information. The introduced interactive cognitive model also allows evaluation of the trustworthiness of a source both on the basis of its category and on past direct experience with it, thus selecting the more adequate source with respect to the informative goals to achieve. We present a computational approach based on fuzzy sets and some selected simulation scenarios together with the discussion of their more interesting results. [ABSTRACT FROM AUTHOR]