Multi-Agent–Based Simulation of University Email Communities

2011 ◽  
pp. 273-291
Author(s):  
David Rodrigues
Keyword(s):  
Communication Network ◽  
Network Formation ◽  
Real Data ◽  
Informal Communication ◽  
University Environment ◽  
Agent Based ◽  
Detection Techniques ◽  
The Social ◽  
Multi Agent ◽  
Full Knowledge

In this chapter, a study on informal communication network formation in a university environment is presented. The teacher communication network is analyzed through community detection techniques. It is evident that informal communication is an important process that traverses the vertical hierarchical structure of departments and courses in a university environment. A multi-agent model of the case study is presented here, showing the implications of using real data as training sets for multi-agent-based simulations. The influence of the “social neighborhood,” as a mechanism to create assortative networks of contacts without full knowledge of the network, is discussed. It is shown that the radius of this social neighborhood has an effect on the outcome of the network structure and that in a university’s case this distance is relatively small.

CIUCEU

2009 ◽  
Vol 1 (4) ◽  
pp. 30-48
Author(s):  
David Rodrigues
Keyword(s):  
Communication Network ◽  
Network Formation ◽  
Real Data ◽  
Informal Communication ◽  
University Environment ◽  
Agent Based ◽  
Agent Model ◽  
Detection Techniques ◽  
Multi Agent ◽  
Full Knowledge

In this article, a study on informal communication network formation in a university environment is presented. The teacher communication network is analyzed through community detection techniques. It is evident that informal communication is an important process that traverses the vertical hierarchical structure of departments and courses in a university environment. A multi-agent model of the case study is presented here, showing the implications of using real data as training sets for multi-agent-based simulations. The influence of the “social neighborhood,” as a mechanism to create assortative networks of contacts without full knowledge of the network, is discussed. It is shown that the radius of this social neighborhood has an effect on the outcome of the network structure and that in a university’s case this distance is relatively small.

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

scholarly journals The Dynamic Evolution Mechanism of Heterogeneous OWOM—An Improved Viral Marketing Model

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 140
Author(s):  
Mengjie Liao ◽  
Lin Qi ◽  
Jian Zhang
Keyword(s):  
Social Media ◽  
Negative Impact ◽  
Viral Marketing ◽  
Dynamic Visualization ◽  
Agent Based ◽  
Marketing Model ◽  
Online Word Of Mouth ◽  
The Social ◽  
Huge Impact ◽  
Multi Agent

The negative impact of brand negative online word-of-mouth (OWOM) on social images in social media is far greater than the promotion of positive OWOM. Thus, how to optimize brand image by improving the positive OWOM effect and slowing the negative OWOM communication has turned into an urgent problem for brand enterprises. On this basis, we analyze the evolution process of the OWOM communication group of the social media brand network based on the SOR (stimulus-organism-response) theory of psychology. Through constructing the heterogeneous brand OWOM communication dynamic model and conducting the multi-agent-based simulation experiment, the dynamic visualization of brand OWOM communication effect combined the thinking model of viral marketing is realized. Experiments show that the ability of brand communicators to persuade has a direct impact on the persistence and breadth of brand communication. When the acceptance of the consumer market is high, the negative OWOM of the brand has a relatively huge impact on consumers.

scholarly journals Special Issue on New Trends in Agent-Based Simulation

2011 ◽  
Vol 15 (2) ◽  
pp. 165-165
Author(s):  
Keiki Takadama ◽  
Kiyoshi Izumi
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Computer Science ◽  
Mutual Influence ◽  
Real Data ◽  
Special Issue ◽  
Learning Mechanisms ◽  
Agent Based Simulation ◽  
Agent Based ◽  
The Social

Agent-Based Simulation (ABS), an interdisciplinary area embracing both the computer science and the social science, has attracted much attention and aided the understanding of socially complex phenomena. A current important issue in this research area is how to improve ABS effectiveness and comprehension, which makes further mutual influence between the computer science and the social sciences indispensable - e.g., (1) agent modeling involving learning mechanisms in the computer science and (2) social dynamics analysis needed in the social science. Such integration of these two areas would help fulfill the great potential of ABS, first in solving complex engineering problems using agent-based technology and second in developing and testing new theories on socially complex systems. This special issue features ABS papers from both of these important areas exploring new trends in ABS. The 10 papers composing this special issue start with papers by Nobutada Fujii and Hiroyasu Inoue analyzing the relationship between the network structure and system dynamics. In these papers, an agent-based computational economics approach has been active in applying agent-based technologies to financial and economic systems. Papers by Biliana Alexandrova-Kabadjova, Isamu Okada, TomokoOhi, and Nariaki Nishino cover consumer and financial markets using agent-based models. They test economic theory and examine market phenomena for market design. Agent-based simulation is increasingly used in application fields in the social sciences. Papers by Kiyoshi Izumi, Hideki Fujii, Hiromitsu Hattori, and Shigeo Sagai propose solutions for actual social problems such as injury prevention, traffic, and electrical power. Models are created based on behavior data, and the integration of an agent-based model and real data is a hot topic in this area. As the beginning of these technical papers, this issue starts by a position paper to give an ABS overview for understanding important issues in ABS from an overall viewpoint and for understanding state-of-the-art ABS. The information presented is invaluable in helping readers grasp the important features of ABS.

Analysis and synthesis: multi-agent systems in the social sciences

2012 ◽  
Vol 27 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Robert E. Marks
Keyword(s):  
Social Sciences ◽  
Computer Science ◽  
Common Source ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Social ◽  
Analysis And Synthesis ◽  
Multi Agent ◽  
Computational Systems

AbstractAlthough they flow from a common source, the uses of multi-agent systems (or ‘agent-based computational systems’––ACE) vary between the social sciences and computer science. The distinction can be broadly summarized as analysis versus synthesis, or explanation versus design. I compare and contrast these uses, and discuss sufficiency and necessity in simulations in general and in multi-agent systems in particular, with a computer science audience in mind.

ATTITUDES, IDEOLOGIES AND SELF-ORGANIZATION: INFORMATION LOAD MINIMIZATION IN MULTI-AGENT DECISION MAKING

2013 ◽  
Vol 16 (02n03) ◽  
pp. 1350029 ◽  
Author(s):  
KIRSTY KITTO ◽  
FABIO BOSCHETTI
Keyword(s):  
Geometric Model ◽  
Physical Sciences ◽  
Individual Agent ◽  
Agent Based ◽  
Modeling Methodology ◽  
Starting Point ◽  
The Social ◽  
Computational Implementation ◽  
Multi Agent ◽  
Attitude Changes

Sophisticated models of human social behavior are fast becoming highly desirable in an increasingly complex and interrelated world. Here, we propose that rather than taking established theories from the physical sciences and naively mapping them into the social world, the advanced concepts and theories of social psychology should be taken as a starting point, and used to develop a new modeling methodology. In order to illustrate how such an approach might be carried out, we attempt to model the low elaboration attitude changes of a society of agents in an evolving social context. We propose a geometric model of an agent in context, where individual agent attitudes are seen to self-organize to form ideologies, which then serve to guide further agent-based attitude changes. A computational implementation of the model is shown to exhibit a number of interesting phenomena, including a tendency for a measure of the entropy in the system to decrease, and a potential for externally guiding a population of agents toward a new desired ideology.

A Versatile Multi-Agent Traffic Simulator Framework Based on Real Data

2016 ◽  
Vol 25 (01) ◽  
pp. 1660006 ◽  
Author(s):  
Alexandre Bonhomme ◽  
Philippe Mathieu ◽  
Sébastien Picault
Keyword(s):  
Decision Support ◽  
Road Traffic ◽  
Real Data ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Traffic Conditions ◽  
Prototype Tool ◽  
Microscopic Models ◽  
Wide Range ◽  
Multi Agent

Among real-system applications of AI, the field of traffic simulation makes use of a wide range of techniques and algorithms. Especially, microscopic models of road traffic have been expanding for several years. Indeed, Multi-Agent Systems provide the capability of modeling the very diversity of individual behaviors. Several professional tools provide comprehensive sets of ready-made, accurate behaviors for several kinds of vehicles. The price in such tools is the difficulty to modify the nature of programmed behaviors, and the specialization in a single purpose, e.g. either studying resulting ows, or providing an immersive virtual reality environment. Thus, we advocate for a more exible approach for the design of multi-purpose tools for decision support. Especially, the use of geographical open databases offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. Our proposal also makes decision support systems able to integrate environmental and behavioral modifications in a linear fashion, and to compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and ows. We also describe here the prototype tool that has been implemented according to our design principles.

scholarly journals USING ASSOCIATIVE NETWORKS TO REPRESENT ADOPTERS' BELIEFS IN A MULTIAGENT MODEL OF INNOVATION DIFFUSION

2008 ◽  
Vol 11 (02) ◽  
pp. 261-272 ◽  
Author(s):  
SAMUEL THIRIOT ◽  
JEAN-DANIEL KANT
Keyword(s):  
Innovation Diffusion ◽  
Diffusion Of Innovations ◽  
Social Representations ◽  
Real Data ◽  
Diffusion Models ◽  
Product Launch ◽  
Agent Based Models ◽  
Associative Networks ◽  
Agent Based ◽  
The Social

A lot of agent-based models were built to study diffusion of innovations. In most of these models, beliefs of individuals about the innovation were not represented at all, or in a highly simplified way. In this paper, we argue that representing beliefs could help to tackle problematics identified for diffusion of innovations, like misunderstanding of information, which can lead to diffusion failure, or diffusion of linked inventions. We propose a formalization of beliefs and messages as associative networks. This representation allows one to study the social representations of innovations and to validate diffusion models against real data. It could also make models usable to analyze diffusion prior to the product launch. Our approach is illustrated by a simulation of iPod™ diffusion.

scholarly journals Spatiotemporal Modeling of the Smart City Residents’ Activity with Multi-Agent Systems

2019 ◽  
Vol 9 (10) ◽  
pp. 2059 ◽  
Author(s):  
Robert Olszewski ◽  
Piotr Pałka ◽  
Agnieszka Turek ◽  
Bogna Kietlińska ◽  
Tadeusz Płatkowski ◽  
...  
Keyword(s):  
Smart City ◽  
Social Activity ◽  
Real Data ◽  
Actor Network Theory ◽  
Spatial Arrangement ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
Spatial Objects ◽  
Multi Agent

The article proposes the concept of modeling that uses multi-agent systems of mutual interactions between city residents as well as interactions between residents and spatial objects. Adopting this perspective means treating residents, as well as buildings or other spatial objects, as distinct agents that exchange multifaceted packages of information in a dynamic and non-linear way. The exchanged information may be reinforced or diminished during the process, which may result in changing the social activity of the residents. Utilizing Latour’s actor–network theory, the authors developed a model for studying the relationship between demographic and social factors, and the diversified spatial arrangement and the structure of a city. This concept was used to model the level of residents’ trust spatiotemporally and, indirectly, to study the level of social (geo)participation in a smart city. The devised system, whose test implementation as an agent-based system was done in the GAMA: agent-based, spatially explicit, modeling and simulation platform, was tested on both model and real data. The results obtained for the model city and the capital of Poland, Warsaw, indicate the significant and interdisciplinary analytical and scientific potential of the authorial methodology in the domain of geospatial science, geospatial data models with multi-agent systems, spatial planning, and applied social sciences.

False Alarm Reduction Using Adaptive Agent-Based Profiling

2013 ◽  
Vol 7 (4) ◽  
pp. 53-74 ◽  
Author(s):  
Salima Hacini ◽  
Zahia Guessoum ◽  
Mohamed Cheikh
Keyword(s):  
Intrusion Detection ◽  
High Rate ◽  
False Alarms ◽  
Multi Agent Systems ◽  
Detection Mechanism ◽  
Agent Based ◽  
Detection Techniques ◽  
Adaptive Agent ◽  
Multi Agent ◽  
Alarm Reduction

In this paper the authors propose a new efficient anomaly-based intrusion detection mechanism based on multi-agent systems. New networks are particularly vulnerable to intrusion, they are often attacked with intelligent and skilful hacking techniques. The intrusion detection techniques have to deal with two problems: intrusion detection and false alarms. The issue of false alarms has an important impact on the success of the anomaly-based intrusion detection technologies. The purpose of this paper is to improve their accuracy by detecting real attacks and by reducing the number of unnecessary generated alerts. The authors' intrusion detection mechanism relies on a set of agents to ensure the detection and the adaptation of normal profile to support the legitimate dynamic changes that occur and are the cause of high rate of false alarms.

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