Trust Agent-Based Behavior Induction in Social Networks

In this chapter, the authors describe the relationships between multi-agent systems, social networks, and the Semantic Web within collaborative work; they also review how the integration of multi-agent systems and Semantic Web technologies and techniques can be used to enhance social networks at all scales. The chapter first provides a review of relevant work on the application of agent-based models and abstractions to the key ingredients of our work: collaborative systems, the Semantic Web, and social networks. Then, the chapter discusses the reasons current multi-agent systems and their foreseen evolution might be a fundamental means for the realization of the future Semantic Social Networks. Finally, some conclusions are drawn.

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Using Quantum Agent-Based Simulation to Model Social Networks

Semantic Web Personalization and Context Awareness ◽

10.4018/978-1-61520-921-7.ch005 ◽

2011 ◽

pp. 42-54

Author(s):

C. Bisconti ◽

A. Corallo ◽

M. De Maggio ◽

F. Grippa ◽

S. Totaro

Keyword(s):

Social Networks ◽

Quantum Mechanics ◽

Quantum Physics ◽

Business Processes ◽

Social Dynamics ◽

Social Systems ◽

Many Body ◽

Agent Based ◽

Microscopic Interactions ◽

The Many

This research aims to apply models extracted from the many-body quantum mechanics to describe social dynamics. It is intended to draw macroscopic characteristics of organizational communities starting from the analysis of microscopic interactions with respect to the node model. In this chapter, the authors intend to give an answer to the following question: which models of the quantum physics are suitable to represent the behaviour and the evolution of business processes? The innovative aspects of the project are related to the application of models and methods of the quantum mechanics to social systems. In order to validate the proposed mathematical model, the authors intend to define an open-source platform able to model nodes and interactions within a network, to visualize the macroscopic results through a digital representation of the social networks.

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Insights into the Impact of Social Networks on Evolutionary Games

Applications of Complex Adaptive Systems ◽

10.4018/978-1-59904-962-5.ch012 ◽

2008 ◽

pp. 306-323

Author(s):

Katia Sycara ◽

Paul Scerri ◽

Anton Chechetka

Keyword(s):

Game Theory ◽

Social Networks ◽

Evolutionary Game Theory ◽

Information Diffusion ◽

Large Population ◽

Evolutionary Game ◽

Evolutionary Games ◽

Agent Based ◽

The Social ◽

The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

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