Linking Theory and Empirics: A General Framework to Model Opinion Formation Processes

We introduce a minimal opinion formation model, which is quite flexible and can reproduce a broad variety of the existing micro-influence assumptions and models. At the same time, the model can be easily calibrated on real data, upon which it imposes only a few requirements. From this perspective, our model can be considered as a bridge, connecting theoretical studies on opinion formation models and empirical research on social dynamics. We investigate the model analytically by using mean-field approximation and numerically. Our analysis is exemplified by recently reported empirical data drawn from an online social network. We demonstrate that the model calibrated on these data may reproduce fragmented and polarizing social systems. Furthermore, we manage to generate an artificial society that features properties quantitatively and qualitatively similar to those observed empirically at the macro scale. This ability became possible after we had advanced the model with two important communication features: selectivity and personalization algorithms.

Study on an Artificial Society of Urban Safety Livability Change

Improving the urban livability status has become the core goal of urban development, and reasonable assessment of the urban livability status and impact is crucial. By combining an objective environment with residents’ subjective cognition, an artificial society (urban livability change artificial society; ULC-AS) is constructed. The ULC-AS includes four types of agents, namely, government, family, resident and safety facility management agency agents, and recognizes dynamic interaction among various agents and between agents and the environment. Taking the Futian District of Shenzhen as an example, this paper examines factors such as migrants, birth policies, and government investment. We simulate the interactions among resident satisfaction changes, relocation decision-making behavior and urban safety livability and analyze the change processes and development trends of urban safety livability under multiple scenarios. Our main result indicates that population change and investment construction are important factors affecting urban safety livability. At present, the population of the Futian District is saturated. Therefore, the government must assess the urban safety livability and increase investment in high-demand areas. Through this method, the goals of urban resource allocation optimization and coordinated urban development can be achieved.

Technological and social networks of a pastoralist artificial society: agent-based modeling of mobility patterns

This paper explores the advantages of simulation to raise the question of how digital and social networks affect the mobility in a pastoralist artificial society in the context of environmental degradation. We aim to explore mechanisms and develop scenarios, which are going to be validated through further research. We use a model of a simple pastoralist society in a world without borders to migration by adding the possibility of experiencing the effects of social structures (such as family and friends) and technological networks (e.g., social media). It appears obvious that pastoralist mobility depends on other dimensions as land tenure and traditional knowledge; however, isolating these two effects and experimenting in a simple society allow us to filter the multidimensionality of mobility decisions and concentrate on comparing scenarios in several different social structures and technological network combinations. The results show an expected behavior of more connection and more mobility, and a non-linear emergent behavior where pastoralists wait for a longer amount of time to mobilize when they interact using powerful social and technological networks. This occurs until they decide to move, and then, they mobilize more quickly and strongly than they did when communication was non-existent between them. The literature on migration explains this emergent non-linear behavior.

Autonomy and nomadic Relativism of Digital Identity

The article examines identity in such digital spaces as video games and virtual reality. These digital spaces are defined as interactive artificial environment, autonomous from reality, with its own ontology, scenario, narrative and mythological context. Video games have an immersive experience that is enhanced in virtual reality due to the ability to integrate into the embodiment of the game's model. The type of digital identity that is defined by the video game designer in accordance with narrative and artistic goals is what we call a character. The opposite type is an avatar, it reflects strategies of self-presentation of an individual (user). Digital identity interests us primarily because of the ability to be independent (autonomous) from human physiology and from social categories that are attributed to the user in the real world. Digital identity can be constructed by the individuals in accordance with their preferences, which makes it possible to solve many gender, racial, and age problems. The possibility to integrate into an avatar embodiment and interact with in-game items it reinforces the distance from real embodiment. Moreover, in multiplayer games with the civil roleplay, it can exist in an artificial society and have introspective meaning for another members of the society. Another significant feature of digital identity is the relativism. Digital identity can be relativistic due to the which allow one to have different identities in different games or change the appearance of an avatar in one game during a play time. Autonomy and relativism can be the strategy for the implementation of projects of nomadic identity by Rosi Braidotti and Donna Haraway, in which subject is not sticked to any constants, but constantly defines and redefines oneself through performative acts.

On the Diversity and Classification of information theories of the Project of Artificial Societies

An urgent problem of artificial intelligence and artificial society is the possibility of using so-called nano-bio-info-cognitive technologies for their development. The convergence of such different technologies is itself a complex and complex problem. The article generalizes the problem of classification of scientific theories. Many provisions of this problem have been fragmentarily considered by other authors. The problem itself, in a certain sense, is connected with L. Floridi's well-known problem about the possibility of building a unified information theory. The formulation of the question of the classification of information theories has quite obvious novelty, since in the Russian scientific and educational literature it has already been established for many years to consider the mathematical theory of communication by K. Shannon as the only possible one. This article presents an original classification of well-known theories, concepts and hypotheses related to information.

Agent-based model "Intellectual Russia": a Study of the Level of Labor potential and the Level of Satisfaction in the Regional and Sectoral sections

The creation of an artificial society is an urgent challenge to modern science. Such a model society can be useful in predicting various scenarios for the development of socio-economic processes in a country, depending on various managerial decisions and the reactions of its individual agents to them. One of the methods of implementing such a society is agent-based modeling, which is used to create a system at the level of its individual agents. This article describes an agent-based model, which is an artificial society of Russian citizens. The results of computer experiments are presented, which make it possible to assess the state of industries and regions of the country from the point of view of the level of labor potential and the level of satisfaction.

The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19

Various social policies and strategies have been deliberated and used within many countries to handle the COVID-19 pandemic. Some of those basic ideas are strongly related to the understanding of human social interactions and the nature of disease transmission and spread. In this paper, we present an agent- based approach to model epidemiological phenomena as well as the interventions upon it. We elaborate on micro-social structures such as social-psychological factors and distributed ruling behaviors to grow an artificial society where the interactions among agents may exhibit the spreading of the virus. Capturing policies and strategies during the pandemic, four types of intervention are also applied in society. Emerged macro-properties of epidemics are delivered from sets of simulations, lead to comparisons between each effectivity of the policy/strategy.