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Improved Trust Establishment Performance with Transaction-based Preprocessing

Published onJun 08, 2021
Improved Trust Establishment Performance with Transaction-based Preprocessing
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Abstract

In Multi-Agent Systems, trustees can utilize trust establishment models to help improve their trust with trustors in the environment. This improved trust helps to improve the quality of interactions in the environment and increases the viability of a trustee as an interaction partner. To help current and future trust establishment models become more modular to adapt to changes brought by future research and to introduce a method to allow for improved performance, a generalized trust establishment model architecture is presented. The proposed Generalized Trust Establishment Model is a simplistic model which illustrates how the generalized architecture can be used to design a competent trust establishment model. This model uses the architecture’s newly proposed transaction-level preprocessing module to achieve strong simulation results. This preprocessing module allows a model to fine-tune the amount of resources that will be given to trustors before the transactions occur to help more accurately meet the needs of trustors. Using the preprocessing module, the proposed model better meets a trustor’s needs and achieves a higher average trust in the environment faster than when the pre- processing is not performed. This exhibits that preprocessing is an important technique that can be used by any trust establishment model to improve the models performance.

Article ID: 2021S02

Month: May

Year: 2021

Address: Online

Venue: Canadian Conference on Artificial Intelligence

Publisher: Canadian Artificial Intelligence Association

URL: https://caiac.pubpub.org/pub/t3b3ekal/

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