Modeling of Agent-Based Complex Network to Detect the Trust of Investors in P2P Platform

Yan, Yuwei; Zhang, Jian; Ma, Xiaofeng

doi:10.4018/ijiit.2019040102

Cited by 7 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e second stage is a multi-lateral negotiation between potential editors. It can be known from the multilateral negotiation process that the top ranked in the set list has priority as a potential alliance [20,21]. is is consistent with the agent's goal of pursuing the maximum benefit of the individual.…”

Section: Establishment Of Multiagent Cooperativementioning

confidence: 99%

Multi-Agent-Based Film Editing Collaboration System

Liang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

In order to realize the effective cooperation between editor agents in the film and television editing collaboration system, it is analyzed that the state change of the film and television editing and production process is affected by the cross influence of multiple factors. A single agent can no longer satisfy the current film and television production. From the point of view of system theory, this article constructs the learner agent in the film and television editing system by introducing a new cooperation mechanism—the multi-agent collaborative system model. Collaboration and cooperation between multiple agents and the reinforcement learning between multiple editor agents are realized based on the film and television editing system between multiple agents. The operation mechanism of the separate organization is organized together, cooperates with each other and works in harmony to complete the collaborative effect of the film and television editing system, and can improve the interaction efficiency between the editor agents. Agent film and television editing’s cooperative learning approach allows for successful collaboration among editor agents. The Bayesian technique is utilized in this study to assess the likelihood of effective cooperation between two agents, and a trust model based on this method is presented, making up for the shortcomings of the existing collaborative learning system. The multi-agent collaboration system will be utilized for production in the film and television editing collaboration system. Many of the movie’s scenes and segments are created using computer technology special effects, giving viewers a very unique experience and a feast for the eyes and ears.

show abstract

Section: Establishment Of Multiagent Cooperativementioning

confidence: 99%

Multi-Agent-Based Film Editing Collaboration System

Liang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…For the second problem, this paper proposes a dynamic simulation model using multiagents. Often, a MAS is used to simulate complex systems, such as a supply chain management system (Dharmalingam & Eswaran, 2018;Tan, Jiang, & Wang, 2019;Walczak, 2018;Yan, Zhang, & Ma, 2019). Zhang, Huang, Sun, and Yang (2014) presented an overall architecture of multiagent-based real-time production scheduling to close the loop of production planning and control and designed a real-time scheduling agent for manufacturing task scheduling/rescheduling strategy and methods according to their real-time feedback.…”

Section: Proposed Methodologymentioning

confidence: 99%

Dynamic decision support framework for production scheduling using a combined genetic algorithm and multiagent model

Dong

Sugumaran

et al. 2020

Expert Systems

View full text Add to dashboard Cite

Due to the dynamic nature, complexity, and interactivity of production scheduling in an actual business environment, suitable combined and hybrid methods are necessary. This paper takes prefabricated concrete components as an example and develops the dynamic decision support framework based on a genetic algorithm and multiagent system (MAS) to optimize and simulate the production scheduling. First, a multiobjective genetic algorithm is integrated into the MAS for preliminary optimization and a series of near-optimal solutions are obtained. Subsequently, considering the resource constraints and uncertainties, the MAS is used to simulate complex realworld production environments. Considering the different types of uncertainty factors, the paper proposes the corresponding dynamic scheduling method and uses MAS to generate the optimal production schedule. Finally, a practical prefabricated construction case is used to validate the proposed model. The results show that the model can effectively address the occurrence of uncertain events and can provide dynamic decision support for production scheduling. Highlights • A dynamic decision support framework based on a genetic algorithm and multiagent system (MAS) for production scheduling is proposed. • A variety of agents are set up in the MAS to increase the likeness of the experimental environment to the real production environment. • Dynamic scheduling methods are proposed for different uncertain factors, and the effectiveness of the proposed method is verified by experiments.

show abstract

An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain

Jing

Choo

et al. 2019

Inf Syst Front

View full text Add to dashboard Cite

Modeling of Agent-Based Complex Network to Detect the Trust of Investors in P2P Platform

Cited by 7 publications

References 15 publications

Multi-Agent-Based Film Editing Collaboration System

Multi-Agent-Based Film Editing Collaboration System

Dynamic decision support framework for production scheduling using a combined genetic algorithm and multiagent model

An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain

Contact Info

Product

Resources

About