Communication and trust in the bounded confidence model

The communication process in a situation of emergency is discussed within the Scheff theory of shame and pride. The communication involves messages from media and from other persons. Three strategies are considered: selfish (to contact friends), collective (to join other people) and passive (to do nothing). We show that the pure selfish strategy cannot be evolutionarily stable. The main result is that the community structure is statistically meaningful only if the interpersonal communication is weak.Comment: 6 pages, 5 figures, RevTeX, for ICCCI-201

Bounded Confidence Evolution of Opinions and Actions in Social Networks

This work was supported in part by the National Natural Science Foundation of China under Grant 71991460, Grant 71991465, Grant 71871149, Grant 71910107002, and Grant 71725001; in part by the Research Foundation of Education Bureau of Hunan Province, China, under Grant 20B147; and in part by the Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/10.13039/501100011033.Inspired by the continuous opinion and discrete action (CODA) model, bounded confidence and social networks, the bounded confidence evolution of opinions and actions in social networks is investigated and a social network opinions and actions evolutions (SNOAEs) model is proposed. In the SNOAE model, it is assumed that each agent has a CODA for a certain issue. Agents’ opinions are private and invisible, that is, an individual agent only knows its own opinion and cannot obtain other agents’ opinions unless there is a social network connection edge that allows their communication; agents’ actions are public and visible to all agents and impact other agents’ actions. Opinions and actions evolve in a directed social network. In the limitation of the bounded confidence, other agents’ actions or agents’ opinions noticed or obtained by network communication, respectively, are used by agents to update their opinions. Based on the SNOAE model, the evolution of the opinions and actions with bounded confidence is investigated in social networks both theoretically and experimentally with a detailed simulation analysis. Theoretical research results show that discrete actions can attract agents who trust the discrete action, and make agents to express extreme opinions. Simulation experiments results show that social network connection probability, bounded confidence, and the opinion threshold of action choice parameters have strong impacts on the evolution of opinions and actions. However, the number of agents in the social network has no obvious influence on the evolution of opinions and actions.National Natural Science Foundation of China (NSFC) 71991460 71991465 71871149 71910107002 71725001Research Foundation of Education Bureau of Hunan Province, China 20B147Spanish Government PID2019-103880RB-I00/AEI/10.13039/50110001103

Significant Role of Trust and Distrust in Social Simulation

This paper introduces the Trust-Distrust Model and its applications, extending the Bounded Confidence Model, a theory of opinion dynamics, to include the relationship between trust and mistrust. In recent years, there has been an increase in the number of cases in which the prerequisites for conventional communication (e.g., the other person’s gender, appearance, tone of voice, etc.) cannot be established without the exchange of personal information. However, in recent years, there has been an increase in the use of personal information, such as letters and pictograms “as cryptographic asset data” for two-way communication. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. In the future, the discussion of trust value in the above data will accelerate in indicators such as personal credit scoring. In this paper, the Trust-Distrust Model will be discussed with respect to theories that also address charismatic people, the effects of advertising, and social divisions. Furthermore, simulations of the Trust-Distrust Model show that 55% agreement is sufficient to build social consensus. By addressing this theory, we hope to use it to discuss and predict social risk in future credit scoring discussions

Resilient Autonomous Control of Distributed Multi-agent Systems in Contested Environments

An autonomous and resilient controller is proposed for leader-follower multi-agent systems under uncertainties and cyber-physical attacks. The leader is assumed non-autonomous with a nonzero control input, which allows changing the team behavior or mission in response to environmental changes. A resilient learning-based control protocol is presented to find optimal solutions to the synchronization problem in the presence of attacks and system dynamic uncertainties. An observer-based distributed H_infinity controller is first designed to prevent propagating the effects of attacks on sensors and actuators throughout the network, as well as to attenuate the effect of these attacks on the compromised agent itself. Non-homogeneous game algebraic Riccati equations are derived to solve the H_infinity optimal synchronization problem and off-policy reinforcement learning is utilized to learn their solution without requiring any knowledge of the agent's dynamics. A trust-confidence based distributed control protocol is then proposed to mitigate attacks that hijack the entire node and attacks on communication links. A confidence value is defined for each agent based solely on its local evidence. The proposed resilient reinforcement learning algorithm employs the confidence value of each agent to indicate the trustworthiness of its own information and broadcast it to its neighbors to put weights on the data they receive from it during and after learning. If the confidence value of an agent is low, it employs a trust mechanism to identify compromised agents and remove the data it receives from them from the learning process. Simulation results are provided to show the effectiveness of the proposed approach

MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy

Understanding collaborative supply chain relationships through the application of the Williamson organisational failure framework

Many researchers have studied supply chain relationships however, the preponderance of open markets situations and ‘industry-style’ surveys have reduced the empirical focus on the dynamics of long-term, collaborative dyadic relationships. Within the supply chain the need for much closer, long-term relationships is increasing due to supplier rationalisation and globalisation (Spekman et al, 1998) and more information about these interactions is required. The research specifically tested the well-accepted Williamson’s (1975) Economic Organisations Failure Framework as a theoretical model through which long term collaborative relationships can be

The Bounded Confidence Model Of Opinion Dynamics

The bounded confidence model of opinion dynamics, introduced by Deffuant et al, is a stochastic model for the evolution of continuous-valued opinions within a finite group of peers. We prove that, as time goes to infinity, the opinions evolve globally into a random set of clusters too far apart to interact, and thereafter all opinions in every cluster converge to their barycenter. We then prove a mean-field limit result, propagation of chaos: as the number of peers goes to infinity in adequately started systems and time is rescaled accordingly, the opinion processes converge to i.i.d. nonlinear Markov (or McKean-Vlasov) processes; the limit opinion processes evolves as if under the influence of opinions drawn from its own instantaneous law, which are the unique solution of a nonlinear integro-differential equation of Kac type. This implies that the (random) empirical distribution processes converges to this (deterministic) solution. We then prove that, as time goes to infinity, this solution converges to a law concentrated on isolated opinions too far apart to interact, and identify sufficient conditions for the limit not to depend on the initial condition, and to be concentrated at a single opinion. Finally, we prove that if the equation has an initial condition with a density, then its solution has a density at all times, develop a numerical scheme for the corresponding functional equation, and show numerically that bifurcations may occur.Comment: 43 pages, 7 figure

Consumer trust and willingness to pay for certified animal-friendly products

Increasing animal welfare standards requires changes along the supply chain which involve several stakeholders: scientists, farmers and people involved in transportation and slaughtering. The majority of researchers agree that compliance with these standards increases costs along the livestock value chain, especially for monitoring and certifying animal-friendly products. Knowledge of consumer willingness to pay (WTP) in such a decision context is paramount to understanding the magnitude of market incentives necessary to compensate all involved stakeholders. The market outcome of certification programs is dependent on consumer trust. Particularly, there is a need to understand to what extent consumers believe that stakeholders operating in the animal-friendly supply chain will respect certification standards. We examine these issues using a contingent valuation survey administered in five economically dominant EU countries. The implied WTP estimates are found to be sensitive to robust measures of consumer trust for certified animal-friendly products. Significant differences across countries are discussed