All issues

The paper considers the application of swarm intelligence technology to build agent-based simulation models. As an example, a minimal model is constructed illustrating the influence of information influences on the rules of behavior of agents in the simplest model of competition between two populations, whose agents perform the simplest task of transferring a resource from a mobile source to their territory. The algorithm for the movement of agents in the model space is implemented on the basis of the classical particle swarm algorithm. Agents have a life cycle, that is, the processes of birth and death are taken into account. The model takes into account information processes that determine the target functions of the behavior of newly appeared agents. These processes (training and poaching) are determined by information influences from populations. Under certain conditions, a third population arises in the agent system. Agents of such a population informatively influence agents of other populations in a certain radius around themselves, changing.

As a result of the conducted simulation experiments, it was shown that the following final states are realized in the system: displacement of a new population by others, coexistence of a new population and other populations and the absence of such a population. It has been shown that with an increase in the radius of influence of agents, the population with changed rules of behavior displaces all others. It is also shown that in the case of a hard-to-access resource, the strategy of luring agents of a competing population is more profitable.

An effective regional policy in order to stabilize production is impossible without an analysis of the dynamics of economic processes taking place. This article focuses on developing a mathematical model reflecting the interaction of several economic agents with regard to their interests. Developing such a model and its study can be considered as an important step in solving theoretical and practical problems of managing growth.

In this paper we consider mathematical model to control water quality. We study a system with two-level hierarchy: one environmental organization (supervisor) at the top level and a few industrial enterprises (agents) at the lower level. The main goal of the supervisor is to keep water pollution level below certain value, while enterprises pollute water, as a side effect of the manufacturing process. Supervisor achieves its goal by charging a penalty for enterprises. On the other hand, enterprises choose how much to purify their wastewater to maximize their income.The fee increases the budget of the supervisor. Moreover, effulent fees are charged for the quantity and/or quality of the discharged pollution. Unfortunately, in practice, such charges are ineffective due to the insufficient tax size. The article solves the problem of determining the optimal size of the charge for pollution discharge, which allows maintaining the quality of river water in the rear range.

We describe system members goals with target functionals, and describe water pollution level and enterprises state as system of ordinary differential equations. We consider the problem from both supervisor and enterprises sides. From agents’ point a normal-form game arises, where we search for Nash equilibrium and for the supervisor, we search for Stackelberg equilibrium. We propose numerical algorithms for finding both Nash and Stackelberg equilibrium. When we construct Nash equilibrium, we solve optimal control problem using Pontryagin’s maximum principle. We construct Hamilton’s function and solve corresponding system of partial differential equations with shooting method and finite difference method. Numerical calculations show that the low penalty for enterprises results in increasing pollution level, when relatively high penalty can result in enterprises bankruptcy. This leads to the problem of choosing optimal penalty, which requires considering problem from the supervisor point. In that case we use the method of qualitatively representative scenarios for supervisor and Pontryagin’s maximum principle for agents to find optimal control for the system. At last, we compute system consistency ratio and test algorithms for different data. The results show that a hierarchical control is required to provide system stability.

The article describes a simulation agent-based model of intercultural interactions in a country whose population belongs to different cultures. It is believed that the space of cultures can be represented as a Hilbert space, in which certain subspaces correspond to different cultures. In the model, the concept of culture is understood as a structured subspace of the Hilbert space. This makes it possible to describe the state of agents by a vector in a Hilbert space. It is believed that each agent is described by belonging to a certain «culture». The number of agents belonging to certain cultures is determined by demographic processes that correspond to these cultures, the depth and integrity of the educational process, as well as the intensity of intercultural contacts. Interaction between agents occurs within clusters, into which, according to certain criteria, the entire set of agents is divided. When agents interact according to a certain algorithm, the length and angle that characterize the state of the agent change. In the process of imitation, depending on the number of agents belonging to different cultures, the intensity of demographic and educational processes, as well as the intensity of intercultural contacts, aggregates of agents (clusters) are formed, the agents of which belong to different cultures. Such intercultural clusters do not entirely belong to any of the cultures initially considered in the model. Such intercultural clusters create uncertainties in cultural dynamics. The paper presents the results of simulation experiments that illustrate the influence of demographic and educational processes on the dynamics of intercultural clusters. The issues of the development of the proposed approach to the study (discussion) of the transitional states of the development of cultures are discussed.

The article deals with the modeling of the number of employed population by branches of the economy at the national and regional levels. The lack of targeted distribution of workers in a market economy requires the study of systemic processes in the labor market that lead to different dynamics of the number of employed in the sectors of the economy. In this case, personal strategies for choosing labor activity by economic agents become important. The presence of different strategies leads to the emergence of strata in the labor market with a dynamically changing number of employees, unevenly distributed among the sectors of the economy. As a result, non-linear fluctuations in the number of employed population can be observed, the toolkit of agentbased modeling is relevant for the study of the fluctuations. In the article, we examined in-phase and anti-phase fluctuations in the number of employees by economic activity on the example of the Jewish Autonomous Region in Russia. The fluctuations found in the time series of statistical data for 2008–2016. We show that such fluctuations appear by age groups of workers. In view of this, we put forward a hypothesis that the agent in the labor market chooses a place of work by a strategy, related with his age group. It directly affects the distribution of the number of employed for different cohorts and the total number of employed in the sectors of the economy. The agent determines the strategy taking into account the socio-economic characteristics of the branches of the economy (different levels of wages, working conditions, prestige of the profession). We construct a basic agentoriented model of a three-branch economy to test the hypothesis. The model takes into account various strategies of economic agents, including the choice of the highest wages, the highest prestige of the profession and the best working conditions by the agent. As a result of numerical experiments, we show that the availability of various industry selection strategies and the age preferences of employers within the industry lead to periodic and complex dynamics of the number of different-aged employees. Age preferences may be a consequence, for example, the requirements of employer for the existence of work experience and education. Also, significant changes in the age structure of the employed population may result from migration.

In the present article we explore the process of changing the level of approval of a political leader under the influence of the processes taking place in online platforms (social networks, forums, etc.). The driver of these changes is the interaction of users, through which they can exchange opinions with each other and formulate their position in relation to the political leader. In addition to interpersonal interaction, we will consider such factors as the information impact, expressed in the creation of an information flow with a given power and polarity (positive or negative, in the context of influencing the image of a political leader), as well as the presence of a group of agents (opinion leaders), supporting the leader, or, conversely, negatively affecting its representation in the media space.

The mathematical basis of the presented research is the Kirman model, which has its roots in biology and initially found its application in economics. Within the framework of this model it is considered that each user is in one of the two possible states, and a Markov jump process describing transitions between these states is given. For the problem under consideration, these states are 0 or 1, depending on whether a particular agent is a supporter of a political leader or not. For further research, we find its diffusional approximation, known as the Jacoby process. With the help of spectral decomposition for the infinitesimal operator of this process we have an opportunity to find an analytical representation for the transition probability density.

Analyzing the probabilities obtained in this way, we can assess the influence of individual factors of the model: the power and direction of the information flow, available to online users and relevant to the tasks of rating formation, as well as the number of supporters or opponents of the politician. Next, using the found eigenfunctions and eigenvalues, we derive expressions for the evaluation of conditional mathematical expectations of a politician’s rating, which can serve as a basis for building forecasts that are important for the formation of a strategy of representing a political leader in the online environment.

This article discusses the influence of the shadow, informal and household sectors on the dynamics of a stochastic model with heterogeneous (heterogeneous) agents. The study uses the integration of the general equilibrium approach to explain the behavior of demand, supply and prices in an economy with several interacting markets, and a multi-agent approach. The analyzed model describes an economy with aggregated uncertainty and with an infinite number of heterogeneous agents (households). The source of heterogeneity is the idiosyncratic income shocks of agents in the legal and shadow sectors of the economy. In the analysis, an algorithm is used to approximate the dynamics of the distribution function of the capital stocks of individual agents — the dynamics of its first and second moments. The synthesis of the agent approach and the general equilibrium approach is carried out using computer implementation of the recursive feedback between microagents and macroenvironment. The behavior of the impulse response functions of the main variables of the model confirms the positive influence of the shadow economy (below a certain limit) on minimizing the rate of decline in economic indicators during recessions, especially for developing economies. The scientific novelty of the study is the combination of a multi-agent approach and a general equilibrium approach for modeling macroeconomic processes at the regional and national levels. Further research prospects may be associated with the use of more detailed general equilibrium models, which allow, in particular, to describe the behavior of heterogeneous groups of agents in the entrepreneurial sector of the economy.

In some cases, information warfare results in almost whole population accepting one of two contesting points of view and rejecting the other. In other cases, however, the “majority party” gets only a small advantage over the “minority party”. The relevant question is which network characteristics of a population contribute to the minority being able to maintain some significant numbers. Given that some societies are more connected than others, in the sense that they have a higher density of social ties, this question is specified as follows: how does the density of social ties affect the chances of a minority to maintain a significant number? Does a higher density contribute to a landslide victory of majority, or to resistance of minority? To address this issue, we consider information warfare between two parties, called the Left and the Right, in the population, which is represented as a network, the nodes of which are individuals, and the connections correspond to their acquaintance and describe mutual influence. At each of the discrete points in time, each individual decides which party to support based on their attitude, i. e. predisposition to the Left or Right party and taking into account the influence of his network ties. The influence means here that each tie sends a cue with a certain probability to the individual in question in favor of the party that themselves currently support. If the tie switches their party affiliation, they begin to agitate the individual in question for their “new” party. Such processes create dynamics, i. e. the process of changing the partisanship of individuals. The duration of the warfare is exogenously set, with the final time point roughly associated with the election day. The described model is numerically implemented on a scale-free network. Numerical experiments have been carried out for various values of network density. Because of the presence of stochastic elements in the model, 200 runs were conducted for each density value, for each of which the final number of supporters of each of the parties was calculated. It is found that with higher density, the chances increase that the winner will cover almost the entire population. Conversely, low network density contributes to the chances of a minority to maintain significant numbers.

One of the principles of forming a competitive market environment is to create conditions for economic agents to implement Nash – Cournot optimal strategies. With the standard approach to determining Nash – Cournot optimal market strategies, economic agents must have complete information about the indicators and dynamic characteristics of all market participants. Which is not true.

In this regard, to find Nash – Cournot optimal solutions in dynamic models, it is necessary to have a coordinator who has complete information about the participants. However, in the case of a large number of game participants, even if the coordinator has the necessary information, computational difficulties arise associated with the need to solve a large number of coupled equations (in the case of linear dynamic games — Riccati matrix equations).

In this regard, there is a need to decompose the general problem of determining optimal strategies for market participants into private (local) problems. Approaches based on the iterative decomposition of coupled matrix Riccati equations and the solution of local Riccati equations were studied for linear dynamic games with a quadratic criterion. This article considers a simpler approach to the iterative determination of the Nash – Cournot equilibrium in an oligopoly, by decomposition using operational calculus (operator method).

The proposed approach is based on the following procedure. A virtual coordinator, which has information about the parameters of the inverse demand function, forms prices for the prospective period. Oligopolists, given fixed price dynamics, determine their strategies in accordance with a slightly modified optimality criterion. The optimal volumes of production of the oligopolists are sent to the coordinator, who, based on the iterative algorithm, adjusts the price dynamics at the previous step.

The proposed procedure is illustrated by the example of a static and dynamic model of rational behavior of oligopoly participants who maximize the net present value (NPV). Using the methods of operational calculus (and in particular, the inverse Z-transformation), conditions are found under which the iterative procedure leads to equilibrium levels of price and production volumes in the case of linear dynamic games with both quadratic and nonlinear (concave) optimization criteria.

The approach considered is used in relation to examples of duopoly, triopoly, duopoly on the market with a differentiated product, duopoly with interacting oligopolists with a linear inverse demand function. Comparison of the results of calculating the dynamics of price and production volumes of oligopolists for the considered examples based on coupled equations of the matrix Riccati equations in Matlab (in the table — Riccati), as well as in accordance with the proposed iterative method in the widely available Excel system shows their practical identity.

In addition, the application of the proposed iterative procedure is illustrated by the example of a duopoly with a nonlinear demand function.

Simulation multiagent model of artificial life was created. Competitive ad-vantages of directed movement and diverse strategies of its using in population of protozoa in illumination gradient were considered. The results consistent with r-K selection theory were obtained. Agents behavior in artificial ecosystem are in qualitative agreement with behavior observed in nature.