Personalised and dynamic trust in social networks

Walter, Frank E.; Battiston, Stefano; Schweitzer, Frank

doi:10.1145/1639714.1639747

Cited by 67 publications

(69 citation statements)

References 20 publications

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“…This basic model is based on the experienced-based trust model described in [14], and applied in [23,24,26]. In an agent's received experience, experiences are taken to be of two forms: direct experiences, for example, by observation, and indirect experiences obtained from communication.…”

Section: Modelling Trust Dynamics From Two Perspectivesmentioning

confidence: 99%

“…The dynamical model takes the form of a system of difference or differential equations for the dynamics of these variables. Well known classical examples of such population-based models are systems of difference or differential equations for predator-prey dynamics [e.g., 4,18,19,26] and the dynamics of epidemics [e.g., 1,4,7,17]. Historically such population level models are specified and studied by simulation and by numerical-mathematical techniques.…”

Section: Introductionmentioning

confidence: 99%

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Agent-Based and Population-Based Modeling of Trust Dynamics

Jaffry

Treur

2013

Transactions on Computational Collective Intelligence IX

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Trust is usually viewed at an individual level in the sense of an agent having trust in a certain trustee. It can also be considered at a population level, in the sense of how much trust for a certain trustee exists in a given population or group of agents. The dynamics of trust states over time can be modelled per individual in an agent-based manner. These individual trust states can be aggregated to obtain the trust state of the population. However, in an alternative way trust dynamics can be modelled from a population perspective as well. Such a population-level model is much more efficient computationally. In this paper both ways of modelling are investigated and it is analyzed how close they can approximate each other. This is done both by simulation experiments and by mathematical analysis. It is shown that the approximation can be reasonably accurate, and for larger numbers of agents even quite accurate.

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Section: Modelling Trust Dynamics From Two Perspectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Agent-Based and Population-Based Modeling of Trust Dynamics

Jaffry

Treur

2013

Transactions on Computational Collective Intelligence IX

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“…Trust became an accredited aspect not only in social, but also in computer science [38][39][40]. Agent-based multisensor BRS is one of the environments where trust is indispensable and plays important roles in (i) helping determine the most reliable interaction partner (i.e., those in which the agent has the highest trust); (ii) influencing the interaction process itself (e.g., an agent's contract stance may vary according to another agent's trust level); (iii) defining the set of issues the need to be settled in the contract (i.e., the higher the trust, the more that can be left implicit in the contract).…”

Section: Constructing Agents Trust Networkmentioning

confidence: 99%

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

Xiong¹,

Zhang²,

Wang³

et al. 2012

IJCIS

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This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP) with high efficiency. We first analyze agent and agent-based simulation framework, CNP and collaborators, and present agents interaction chain used to actualize CNP and establish agents trust network. We then obtain contractor's importance weight and dynamic trust by presenting fuzzy similarity-based algorithm and trust modifying algorithm, thus we propose contractor selecting approach based on maximum dynamic integrative trust. We validate the feasibility and capability of this approach by implementing simulation, analyzing compared results and checking the model.

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“…This basic model is based on the experienced-based trust model described in [1], and applied in [3,4,5]. In the case of communicating agents, experiences are taken to be of two forms: direct experiences acquired, for example, by observation, and indirect experiences, obtained from communication.…”

Section: Modelling Trust Dynamics From Two Perspectivesmentioning

confidence: 99%

Modelling Trust for Communicating Agents: Agent-Based and Population-Based Perspectives

Jaffry

Treur

2011

Computational Collective Intelligence. Technologies and Applications

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Abstract.This paper presents an exploration of the differences between agent-based and population-based models for trust dynamics. This exploration is based on both a large variety of simulation experiments and a mathematical analysis of the equilibria of the two types of models. The outcomes show that the differences between the models are not very substantial, and become less for larger numbers of agents.

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Personalised and dynamic trust in social networks

Cited by 67 publications

References 20 publications

Agent-Based and Population-Based Modeling of Trust Dynamics

Agent-Based and Population-Based Modeling of Trust Dynamics

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

Modelling Trust for Communicating Agents: Agent-Based and Population-Based Perspectives

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