scholarly journals Transitional dynamics in network game with heterogeneous agents: stochastic case

2021 ◽  
Vol 13 (1) ◽  
pp. 102-129
Author(s):  
Алексей Васильевич Королев ◽  
Alexey Korolev
Keyword(s):  
Qualitative Analysis ◽  
Heterogeneous Agents ◽  
Single Agent ◽  
Random Processes ◽  
Stochastic Equations ◽  
Transitional Dynamics ◽  
Network Games ◽  
Network Game ◽  
Stochastic Parameters ◽  
Stochastic Case

In this paper, stochastic parameters are introduced into the network games model with production and knowledges externalities. This model was formulated by V. Matveenko and A. Korolev and generalized two-period Romer model. Agents' productivities have deterministic and Wiener components. The research represents the dynamics of a single agent and the dynamics in a triangle which occurs in the process of unifying agents. Explicit expressions of the dynamics of a single agent and dyad agents in the form of Brownian random processes were obtained. A qualitative analysis of the solutions of stochastic equations and systems was carried out.

scholarly journals Efficiency and Equilibrium in Network Games: An Experiment

2021 ◽  
pp. 1-44
Author(s):  
Edoardo Gallo ◽  
Chang Yan
Keyword(s):  
Nash Equilibrium ◽  
Network Structure ◽  
Economic Systems ◽  
Central Feature ◽  
Network Games ◽  
Trade Off ◽  
Network Game ◽  
Asymmetric Networks ◽  
Unique Nash Equilibrium

Abstract The tension between efficiency and equilibrium is a central feature of economic systems. We examine this trade-off in a network game with a unique Nash equilibrium in which agents can achieve a higher payoff by following a “collaborative norm”. Subjects establish and maintain a collaborative norm in the circle, but the norm weakens with the introduction of one hub connected to everyone in the wheel. In complex and asymmetric networks of 15 and 21 nodes, the norm disappears and subjects’ play converges to Nash. We provide evidence that subjects base their decisions on their degree, rather than the overall network structure.

scholarly journals Identifying the Salient Genes in Microarray Data: A Novel Game Theoretic Model for the Co-Expression Network

Diagnostics ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 586
Author(s):  
Papori Neog Bora ◽  
Vishwa Jyoti Baruah ◽  
Surajit Borkotokey ◽  
Loyimee Gogoi ◽  
Priyakshi Mahanta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Diseases ◽  
System Level ◽  
Theoretic Model ◽  
Cancer Dataset ◽  
Network Games ◽  
Diagnosis And Prognosis ◽  
Network Game ◽  
Game Theoretic ◽  
Relevance Index

Microarray techniques are used to generate a large amount of information on gene expression. This information can be statistically processed and analyzed to identify the genes useful for the diagnosis and prognosis of genetic diseases. Game theoretic tools are applied to analyze the gene expression data. Gene co-expression networks are increasingly used to explore the system-level functionality of genes, where the roles of the genes in building networks in addition to their independent activities are also considered. In this paper, we develop a novel microarray network game by constructing a gene co-expression network and defining a game on this network. The notion of the Link Relevance Index (LRI) for this network game is introduced and characterized. The LRI successfully identifies the relevant cancer biomarkers. It also enables identifying salient genes in the colon cancer dataset. Network games can more accurately describe the interactions among genes as their basic premises are to consider the interactions among players prescribed by a network structure. LRI presents a tool to identify the underlying salient genes involved in cancer or other metabolic syndromes.

Trade with Technology Spillover: A Dynamic Network Game Analysis

2020 ◽  
pp. 2050011
Author(s):  
David W. K. Yeung ◽  
Leon A. Petrosyan ◽  
Yingxuan Zhang
Keyword(s):  
Shapley Value ◽  
General Class ◽  
Dynamic Network ◽  
Technology Spillover ◽  
Network Games ◽  
Game Analysis ◽  
The Shapley Value ◽  
Positive Externalities ◽  
Network Game ◽  
Representative Model

This paper presents a general class of dynamic network games to analyze trade with technology spillover. Due to the fact that the benefits of technology spillover are not fully accrued to the technology developer, the positive externalities are under-exploited. The cooperative solution yields an optimal outcome. To reflect the contributions of individual agents to the network, the Shapley value is used as a solution optimality principle in sharing the cooperative gains. A time-consistent payoff imputation procedure is derived to maintain the Shapley value at each stage of the cooperation. A representative model based on the general class of network games with explicit functional form is given. This is the first time that trade with technology spillover is studied in the framework of dynamic network games, further studies along this line are expected.

Predicting the Usage Intention of Social Network Games

2013 ◽  
pp. 195-204
Author(s):  
Chiao-Chen Chang ◽  
Yang-Chieh Chin
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Technology Acceptance ◽  
Extrinsic Motivation ◽  
Network Games ◽  
User Intention ◽  
Personal Innovativeness ◽  
Personal Involvement ◽  
Network Game ◽  
Acceptance Model

Social network sites (SNSs) are new communication channels with which people can share information. The main functions of SNSs, such as MySpace, Facebook, and Orkut, consist of displaying a user’s social contacts, enabling people to view each other’s social networks and search for common friends or interesting content. Social networks are also connected to gaming and it is quickly becoming one of the most popular categories of applications on SNSs. The goal of this project is to gain insight into the factors that affect user intention to use a social network game. The study uses an extended technology acceptance model and focuses on combining personal innovativeness, personal involvement, intrinsic motivation and extrinsic motivation to explain usage intentions for social network games. The proposed model was tested with data collected from potential users of a social network game. A multiple regression analysis and MANOVA analysis were then conducted to identify the key causal relationships. It is expected that personal innovativeness and personal involvement will have positive effects on intrinsic and extrinsic motivation and ultimately influence usage intentions with regard to social network games.

Moving Beyond Churn: Barriers and Constraints to Playing a Social Network Game

2018 ◽  
Vol 14 (2) ◽  
pp. 170-189 ◽  
Author(s):  
Kelly Bergstrom
Keyword(s):  
Social Network ◽  
Social Networking ◽  
Leisure Time ◽  
Social Networking Site ◽  
Network Games ◽  
External Constraints ◽  
Network Game ◽  
Casual Games

Social network games (SNGs) are genre of casual games that require being logged into a social networking site (e.g., Facebook) to access the gameworld. To date, investigations of these games are typically focused on the rate of attrition or “churn,” reinforcing the idea that SNG players exist to make the developer money rather than participating in a game they derive pleasure from. Seeking to recenter the player in research about SNGs, this article reports on a survey of former players ( N = 147) who were queried about their reason(s) for no longer participating in YoWorld, a Facebook-based SNG. Findings indicate that players typically quit because of external constraints to their leisure time rather than no longer interested in the game, which are not barriers to play that can be overcome by personalized in-game incentives, the typical developer response to prevent churn from taking place.

scholarly journals Максимум энтропии в масштабно-инвариантных процессах с 1/f-=SUP=-alpha-=/SUP=--спектром мощности: влияние анизотропии белого шума

2019 ◽  
Vol 45 (9) ◽  
pp. 19
Author(s):  
В.П. Коверда ◽  
В.Н. Скоков
Keyword(s):  
Phase Transitions ◽  
White Noise ◽  
Power Spectra ◽  
Random Processes ◽  
Stochastic Equations ◽  
Alpha Power ◽  
Entropy Maximum ◽  
The Stability ◽  
Nonlinear Stochastic Equations

Large value fluctuations are modeled by a system of nonlinear stochastic equations describing the interacting phase transitions. Under the action of anisotropic white noise, random processes are formed with the 1/f^alpha dependence of the power spectra on frequency at values of the exponent from 0.7 to 1.7. It is shown that fluctuations with 1/f^alpha power spectra in the studied range of changes correspond to the entropy maximum, which indicates the stability of processes with 1/f^alpha power spectra at different values of the exponent alpha.

Effect of Self-Directed Learning Readiness by Learner’s Interaction on Social Network Games

2013 ◽  
Vol 15 (3) ◽  
pp. 47-60
Author(s):  
Hyungsung Park
Keyword(s):  
Social Network ◽  
Learning Activity ◽  
Meaningful Difference ◽  
Self Directed Learning ◽  
Network Games ◽  
Learning Readiness ◽  
Four Dimensions ◽  
Network Game ◽  
Directed Learning ◽  
Gaming Activity

The purpose of this study is to find the educational meaning of activity on social network games. It was explored whether social network games can be used effectively to support learning via focusing on interaction. Social network games have a structure to facilitate self-directed learning readiness that is the nature of game-learning activity in terms of four dimensions. Four types of interaction on game learning activity are as follows: player-corresponding player interaction, player-content interaction, player-NPC (non-player character or game system) interaction, and player-context interaction. The result of this research, there are meaningful difference of self-directed learning readiness between learners who perform social network games and did not perform in their effect on the student's self-directed learning readiness on social network gaming activity. In other words, the group that performed the experience activity on social network game of higher interaction experienced improving of self-directed learning readiness than the group that did not perform the game.

Interaction to Facilitate Learning in Social Network Gaming

2013 ◽  
pp. 145-161
Author(s):  
Hyungsung Park
Keyword(s):  
Social Network ◽  
Learning Process ◽  
Learning Activity ◽  
Network Games ◽  
Interaction Structure ◽  
Related Literature ◽  
Four Dimensions ◽  
Network Game ◽  
Content Interaction

This chapter explores whether social network games can be used effectively to support learning via focusing on interaction. The aim of this chapter is to find an interaction structure to facilitate learning on social network games by analyzing the nature of game-learning activity in terms of four dimensions. To this end, the types of interaction which can be applied in a game learning process through previous studies and related literature are suggested. The four types of interaction in game learning activity are as follows: Player-Corresponding Player interaction (PCP), Player-Content interaction (PC), player-NPC (non-player character or game system in social network game) interaction, and player-context interaction. Pioneer Trail, a social network game by Zynga and linked via Facebook, was analyzed in terms of suggested interaction formats.

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