Power System Based on Multi-Agent Technology

2013 ◽  
Vol 273 ◽  
pp. 276-279
Author(s):  
Xiao Zhou Fan
Keyword(s):  
Artificial Intelligence ◽  
Power System ◽  
Open System ◽  
Large Scale ◽  
Distributed Artificial Intelligence ◽  
Computer Networking ◽  
Agent Technology ◽  
Large Power ◽  
Complex Problems ◽  
Multi Agent

Multi-agent technology combines the technology of computer, networking and distributed artificial intelligence together which is good at solving complex problems about large-scale distributed and open system. Multi-agent technology provides new ways for power system studies. This paper aims at finding a way to rationally use the multi-agent technology to solve complex problems due to improper protection or slow even wrong actions in the large power system.

Distributed Remote Monitoring System Key Technology Research on Agent

2013 ◽  
Vol 860-863 ◽  
pp. 2774-2782
Author(s):  
Peng Liang Lv ◽  
Guo Shun Chen
Keyword(s):  
Artificial Intelligence ◽  
Traffic Control ◽  
Computer Network ◽  
Distributed Artificial Intelligence ◽  
Agent Technology ◽  
High Tech ◽  
Technology Research ◽  
Artificial Intelligence Research ◽  
Remote Monitoring System ◽  
Multi Agent

Recent years, as computer science and the development of high-tech communications networks, distributed artificial intelligence field of artificial intelligence research as an important branch, more and more industry attention. One of the Agent and Multi-Agent technology research became a hot topic of distributed artificial intelligence research. Research on Multi-Agent technology is mainly a group of autonomous distributed open Agent in a dynamic environment, through interaction, cooperation, competition, negotiation and other acts perform complex control or task solving. Because of its better reflect human social intelligence, more suitable for an open, dynamic social environment, thus causing researchers in various fields of interest, and is widely used in scientific computing, computer network e-commerce, business management and traffic control, etc

An Intelligent Security Defensive Model of SCADA Based on Multi-Agent in Oil and Gas Fields

2019 ◽  
Vol 34 (01) ◽  
pp. 2059003
Author(s):  
Li Yang ◽  
Junlin Liu ◽  
Yun Zhang
Keyword(s):  
Large Scale ◽  
Oil And Gas ◽  
Detection Efficiency ◽  
Agent Technology ◽  
Prototype System ◽  
Scada System ◽  
Accurate Detection ◽  
Multi Agent ◽  
Defense Model ◽  
Intelligent Security

Supervisory Control and Data Acquisition (SCADA) system in the modern industrial automation control network is facing an increasing number of serious security threats. In order to meet the security defense requirements of oil and gas SCADA system, an intelligent security defense model based on multi-agent was designed by analyzing the security risks in oil and gas SCADA system and combining the advantages of multi-agent technology in distributed intrusion detection system. First, the whole structure of this model was divided into three layers: monitoring layer, decision layer and control layer. Then, the defense model was verified by C4.5 decision tree algorithm, and obtained a good result. Finally, the security defense prototype system of large-scale oil and gas SCADA system based on this model was realized. Results demonstrate that the application of multi-agent technology in the security defense of oil and gas SCADA system can achieve more comprehensive defense, more accurate detection, which can handle large-scale distributed attacks and improve the robustness and stability of security defenses. This study makes full use of the multi-agent architecture and has the advantage of accurate detection, high detection efficiency and timely response.

On distributed artificial intelligence

1988 ◽  
Vol 3 (1) ◽  
pp. 21-57 ◽  
Author(s):  
Luis Eduardo ◽  
Castillo Hern
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Model ◽  
Intelligent Agents ◽  
Distributed Artificial Intelligence ◽  
Agent Interaction ◽  
Multi Agent

AbstractDistributed Artificial Intelligence has been loosely defined in terms of computation by distributed, intelligent agents. Although a variety of projects employing widely ranging methodologies have been reported, work in the field has matured enough to reveal some consensus about its main characteristics and principles. A number of prominent projects are described in detail, and two general frameworks, theSystem conceptual modeland theagent conceptual model, are used to compare the different approaches. The paper concludes by reviewing approaches to formalizing some of the more critical capabilities required by multi-agent interaction.

scholarly journals Self-Adaptive Swarm System (SASS)

2021 ◽  
Author(s):  
Qin Yang
Keyword(s):  
Artificial Intelligence ◽  
Distributed Artificial Intelligence ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Collective Decisions ◽  
Fourth Level ◽  
Working Together ◽  
Multi Agent ◽  
Communication Planning ◽  
Self Adaptive

Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a principled Multi-Agent Systems (MAS) cooperation framework -- Self-Adaptive Swarm System (SASS) -- to bridge the fourth level automation gap between perception, communication, planning, execution, decision-making, and learning.

scholarly journals Effectiveness of multi-agent technology in three-day campaign for early diagnosis of cutaneous melanoma

2021 ◽  
Vol 9 (3) ◽  
pp. 433-446
Author(s):  
E.Yu. Neretin ◽  
◽  
S.Kh. Sadreyeva ◽  
◽  
Keyword(s):  
Early Diagnosis ◽  
Cutaneous Melanoma ◽  
Large Scale ◽  
Early Stage ◽  
Good Prognosis ◽  
Agent Technology ◽  
Correct Treatment ◽  
Scale Population ◽  
Multi Agent ◽  
Epidemiological Situation

BACKGROUND: Melanoma — is a tumor that in most cases affects the skin and is characterized by an extremely aggressive course and a steadily increasing morbidity in the world. However, diagnosed at an early stage, cutaneous melanoma (CM) has a good prognosis with correct treatment. The results of the diagnosis of CM can be improved by joint the efforts of dermatologists and artificial intelligence (AI). AIM: Cutaneous melanoma is a tumor with an unpredictable course. The article discusses ways to solve the problem of early diagnosis using multi-agent technology and an expert system based on AI. MATERIALS AND METHODS: In a large industrial city with more than three million population, a three-day campaign for the early diagnostics of cutaneous melanoma was carried out, which revealed 4 cases of CM (4.35%) at pT1a stage in 96 patients registered in 2019. A total of 800 people were examined. RESULTS: As a result of diagnostics, the following data were obtained: specificity of self-diagnostics of the region was 6.78% by the inhabitants, 78.89% by dermatologists, and 95.24% by expert oncologists. In prospective quality control of diagnostics within 6 months, such parameters as the sensitivity of diagnosing cutaneous melanoma by oncologists and dermatologists were both 100%. As a result of the study, it was found that the multi-agent technology is necessary to improve the results of CM diagnostics, and also for a more complete assessment of the onco-epidemiological situation, and for forecasting of the necessary resources in the region. CONCLUSIONS: The multi-agent technology can improve diagnostic results, but for a more complete assessment of the onco-epidemiological situation, a large-scale population screening in the region is required.

Multi-Agent Technology Application in the ASCM Model

2013 ◽  
Vol 706-708 ◽  
pp. 2017-2020
Author(s):  
Yi Xian Chai ◽  
Yan Li Xu ◽  
Dan Liu
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Agent Technology ◽  
Management Skills ◽  
Chain Management ◽  
Technology Application ◽  
Agile Supply Chain ◽  
Multi Agent ◽  
Supply Chain Management System

The bottlenecks of supply chain management need to be solved. The development of internet promotes the Agent technology. Internet makes the Agent technology become a powerful tool that breaks through the bottlenecks of the supply chain management skills. With the guidance of system engineering and methods, an agile supply chain management system with Agent technology of artificial intelligence is presented in this paper. The application of Multi-Agent technology in the ASCM model is discussed also. Results indicate that the application of Multi-Agent skill in the ASCM model is a feasible way of thinking and appropriate approach.

Personal Tour

2012 ◽  
pp. 178-189
Author(s):  
Fabiana Lorenzi ◽  
Stanley Loh ◽  
Mara Abel
Keyword(s):  
Artificial Intelligence ◽  
Incomplete Information ◽  
Recommender System ◽  
Local Knowledge ◽  
Knowledge Bases ◽  
Distributed Artificial Intelligence ◽  
Multiple Agents ◽  
Multi Agent ◽  
User Recommendation

This chapter describes the Personal Tour: a multi-agent recommender system designed to help users to find best travel packages according to their preferences. Personal Tour is based on the collaboration of multiple agents exchanging information stored in their local knowledge bases. Based on the paradigm of the Distributed Artificial Intelligence, a user recommendation request is divided into partial recommendations handled by different agents, each one maintaining incomplete information that may be useful to compose a recommendation.

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