Multi-agent modeling and simulation in the AI age

Fan, Wenhui; Chen, Peiyu; Shi, Daiming; Guo, Xudong; Kou, Li

doi:10.26599/tst.2021.9010005

Cited by 24 publications

(9 citation statements)

References 80 publications

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“…erefore, more refinements are needed in the future. Second, readers' paper search is often a multiobjective decision-making problem that involves a number of influencing factors [47][48][49][50][51][52][53][54] in the mobile edge computing environment. We will further improve our proposal by considering these factors.…”

Section: Discussionmentioning

confidence: 99%

Keywords-Driven Paper Recommendation Based on Mobile Edge Computing Environment Framework

Liu

Wang

Ren

et al. 2022

Scientific Programming

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In the cloud computing era, a paper recommender system is usually deployed on the cloud server and return recommendation results to readers directly. However, considering the paper recommender system, processing tremendous paper citation data on the cloud cannot provide fine-grained personalized and real-time recommendations for each reader because these recommended papers from the cloud are far from readers and probably not correlated strongly with each other for helping each reader research further and deeper in the interested field. Recently, the edge-cloud collaboration-based recommender system has been used for releasing parts of the cloud computing task to the edge and provides the recommendation near the client. Based on the edge computing recommender system, a keywords-driven and weight-aware paper recommendation approach is presented, namely, LP-PRk+ w (link prediction-paper recommendation), to enable intelligent, personalized, and efficient paper recommendation services in the mobile edge computing environment. Specifically, the whole paper recommendation process mainly covers two parts: optimizing the existing paper citation graph via introducing a weighted similarity (i.e., building a weighted paper correlation graph) and then recommending a set of correlated papers according to the weighted paper correlation graph and the users’ query keywords. Experiments on a real-world paper correlation dataset, Hep-Th, show the capability of our proposal for improving the paper recommendation performance and its superiority against other related solutions.

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Section: Discussionmentioning

confidence: 99%

Keywords-Driven Paper Recommendation Based on Mobile Edge Computing Environment Framework

Liu

Wang

Ren

et al. 2022

Scientific Programming

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“…− Entropy: used to measure the bits required to embed the amount of data in certain image. It is increases if the distribution of pixel values is large within the gray area and can fellow in (6):…”

Section: Methodsmentioning

confidence: 99%

“…One integrated supports the other for this reason often the tests are different for the same source because of the change in the smart technology of the method. Software agents can be defined as computational programs that have a set of features such as a sense of the interactive environment and changing variables, proactiveness in making decisions, and the independence of agents and beneficiaries, such as choosing certain actions within certain situations to reach the desired goals [6]. Knowledge sharing is also one of the goals to be achieved when working with software agents and competition is one of the options available here.…”

Section: Introductionmentioning

confidence: 99%

Improve steganography system using agents software based on statistical and classification technique

Halboos¹,

Al-Bakry²

2023

Bulletin EEI

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In digital communications, information security is a paramount necessity. In the hiding algorithm, there are three basic parameters: security, capacity, and imperceptibility. Therefore, there are many ways to design the steganography algorithm, such as least significant bit (LSB), discrete wave transformation (DWT), and discrete cosine transform (DCT). The aim of this paper is to improve agent software design based on a steganography system. It proposed an agent system based on a support vector machine (SVM) classifier to hide a secret message in a certain cover image. The common dataset for steganography uses 80% training and 20% testing to get accurate results. Developing an agent system depends on six statistical parameters such as energy, standard deviation, histogram, variance, mean, and entropy. This resulted in features classified by the SVM classifier to predict the best cover image to be nominated for embedding. Worthy results were obtained in terms of imperceptibility, attack, and cover image prediction by statistical issues.

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“…Scientists have conducted extensive research on the clustering phenomenon of various organisms in nature [ 1 ] and put forward the concept of multi-agent systems (MASs). Due to the high robustness of MASs’ distributed coordinated control, they have been widely used in practical engineering, including for UAV and robot formation, satellite orbit control, smart power grid, collaborative monitoring and other fields [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ]; in addition, in-depth theoretical research has been conducted in control theory, physics, computer and other fields [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Periodic Intermittent Adaptive Control with Saturation for Pinning Quasi-Consensus of Heterogeneous Multi-Agent Systems with External Disturbances

Du,

Xu,

Zhang

et al. 2023

Entropy

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A periodic intermittent adaptive control method with saturation is proposed to pin the quasi-consensus of nonlinear heterogeneous multi-agent systems with external disturbances in this paper. A new periodic intermittent adaptive control protocol with saturation is designed to control the internal coupling between the follower agents and the feedback gain between the leader and the follower. In particular, we use the saturation adaptive law: when the quasi-consensus error converges to a certain range, the adaptive coupling edge weight and the adaptive feedback gain will not be updated. Furthermore, we propose three saturated adaptive pinning control protocols. The quasi-consensus is achieved through its own pinning as long as the agents remain connected to each other. Using the Lyapunov function method and inequality technique, the convergence range of the quasi-consensus error of a heterogeneous multi-agent system is obtained. Finally, the rationality of the proposed control protocol is verified through numerical simulation. Theoretical derivation and simulation results show that the novel proposed periodic intermittent adaptive control method with saturation can successfully be used to achieve the pinning of quasi-consensus of nonlinear heterogeneous multi-agent systems.

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Multi-agent modeling and simulation in the AI age

Cited by 24 publications

References 80 publications

Keywords-Driven Paper Recommendation Based on Mobile Edge Computing Environment Framework

Keywords-Driven Paper Recommendation Based on Mobile Edge Computing Environment Framework

Improve steganography system using agents software based on statistical and classification technique

Periodic Intermittent Adaptive Control with Saturation for Pinning Quasi-Consensus of Heterogeneous Multi-Agent Systems with External Disturbances

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