scholarly journals Social Preference, Incomplete Information, and the Evolution of Ultimatum Game in the Small World Networks: An Agent-Based Approach

2010 ◽  
Vol 13 (2) ◽  
Author(s):  
Bo Xianyu
Keyword(s):  
Incomplete Information ◽  
Social Preference ◽  
Ultimatum Game ◽  
Small World ◽  
Small World Networks ◽  
Agent Based

scholarly journals The Influence of Confidence and Social Networks on an Agent-Based Model of Stock Exchange

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mario A. Bertella ◽  
Jonathas N. Silva ◽  
André L. Correa ◽  
Didier Sornette
Keyword(s):  
Social Networks ◽  
Asset Allocation ◽  
Stock Exchange ◽  
Small World ◽  
Small World Networks ◽  
Unequal Distribution ◽  
Volatility Clustering ◽  
Agent Based ◽  
Return Rates ◽  
Network Topologies

This paper aims to investigate the influence of investors’ confidence in their portfolio holding relative to their social group and of various social network topologies on the dynamics of an artificial stock exchange. An investor’s confidence depends on the growth rate of his or her wealth relative to his or her social group’s average wealth. If the investor’s confidence is low, the agent will change his or her asset allocation; otherwise, he or she will maintain it. We consider three types of social networks: Barabási, small-world, and random. The actual stock markets’ properties are recovered by this model: high excess kurtosis, skewness, volatility clustering, random walk prices, and stationary return rates. The networks’ topologies are found to impact both the structuration of investors in the space of strategies and their performance. Among other characteristics, we find that (i) the small-world networks show the highest degree of homophily; (ii) as investors can switch to more profitable strategies, the best approach to make profitable investments is the chartist one in Barabási and small-world topologies; and (iii) an unequal distribution and more significant relative wealth gains occur in the Barabási network.

Small-world networks and synchronisation in an agent-based model of civil violence

Global Crime ◽  
2019 ◽  
Vol 20 (3-4) ◽  
pp. 161-195
Author(s):  
Maria Fonoberova ◽  
Igor Mezić ◽  
Jadranka Mezić ◽  
James Hogg ◽  
Jason Gravel
Keyword(s):  
Small World ◽  
Small World Networks ◽  
Agent Based Model ◽  
Agent Based ◽  
Civil Violence

scholarly journals Tax Evasion and Multi-Agent-Based Model on Various Topologies

2017 ◽  
Vol 01 (02) ◽  
pp. 1730001
Author(s):  
F. W. S. Lima
Keyword(s):  
Monte Carlo ◽  
Tax Evasion ◽  
Majority Vote ◽  
Small World ◽  
Stat Phys ◽  
Small World Networks ◽  
Vote Model ◽  
Agent Based ◽  
Multi Agent ◽  
Economics Model

In this work, we use Monte-Carlo simulations to study the control of the fluctuations for tax evasion in the economics model proposed by [G. Zaklan, F. Westerhoff and D. Stauffer, J. Econ. Interact. Coordination. 4 (2009) 1; G. Zaklam, F.W.S. Lima and F. Westerhofd, Physica A 387 (2008) 5857.] via a nonequilibrium model with two states ([Formula: see text]) and a noise [Formula: see text] proposed for [M. J. Oliveira, J. Stat. Phys. 66 (1992) 273] and known as Majority-Vote model (MVM) and Sánchez–López-Rodríguez model on communities of agents or persons on some topologies as directed and undirected Barabási–Albert networks and Erdös–Rényi random graphs, Apollonian networks, directed small-world networks and Stauffer–Hohnisch–Pittnauer networks. The MVM is applied around the noise critical [Formula: see text] to evolve the Zaklan model.

Networks

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Complex Systems ◽  
Complex Networks ◽  
Phase Diagrams ◽  
Community Detection ◽  
Network Science ◽  
Small World ◽  
Small World Networks ◽  
Multilayer Networks ◽  
Basic Vocabulary

Understanding the interactions between the components of a system is key to understanding it. In complex systems, interactions are usually not uniform, not isotropic and not homogeneous: each interaction can be specific between elements.Networks are a tool for keeping track of who is interacting with whom, at what strength, when, and in what way. Networks are essential for understanding of the co-evolution and phase diagrams of complex systems. Here we provide a self-contained introduction to the field of network science. We introduce ways of representing and handle networks mathematically and introduce the basic vocabulary and definitions. The notions of random- and complex networks are reviewed as well as the notions of small world networks, simple preferentially grown networks, community detection, and generalized multilayer networks.

scholarly journals Multifractal analysis of eigenvectors of small-world networks

2021 ◽  
Vol 144 ◽  
pp. 110745
Author(s):  
Ankit Mishra ◽  
Jayendra N. Bandyopadhyay ◽  
Sarika Jalan
Keyword(s):  
Multifractal Analysis ◽  
Small World ◽  
Small World Networks
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