A Simulation Approach for Analyzing MAS Model of SIS

2012 ◽  
Vol 468-471 ◽  
pp. 173-180
Author(s):  
Yi Ning Song ◽  
Zhi Li
Keyword(s):  
Information System ◽  
Modeling And Simulation ◽  
Longitudinal Analysis ◽  
Satellite System ◽  
Model Structure ◽  
Multi Agent System ◽  
Simulation Approach ◽  
Agent System ◽  
Agent Model ◽  
Multi Agent

The purpose of this paper is to explore the effective approach of Multi-Agent system(MAS) modeling and simulation. A detailed study of modeling and simulation of Space Information System has been carried out by combining controlled and intelligent requirements. To begin with we will provide a brief background on the Multi-Agent System concept and structure. Furthermore, grasp the model structure through vertical and longitudinal analysis with the consideration of emergence and collaboration. In addition, we described the Multi-agent model for Space Information System(SIS). Finally, algorithms of realizing the collaboration structures of the communication satellite system that presented in this paper were described.

Ontology and Terminology Servers in Agent-based Health-care Information Systems

1997 ◽  
Vol 36 (01) ◽  
pp. 30-43 ◽  
Author(s):  
G. Lanzola ◽  
M. Stefanelli ◽  
S. Falasconi
Keyword(s):  
Health Care ◽  
Information System ◽  
Distributed Applications ◽  
Multi Agent System ◽  
Health Care Information ◽  
Agent System ◽  
Semantic Coherence ◽  
Architectural Framework ◽  
Care Information ◽  
Multi Agent

Abstract:A new research paradigm is emerging based on the multi-agent system architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. Within a multi-agent system, the different “views of the world” of knowledgeable agents are to be bridged through their commitment to common ontologies and terminologies. We developed a general methodology for the design or integration of new components into a Health-care Information System conceived as a network of software and human agents. In our view, ontological and terminological services are entrusted to dedicated agents, namely ontology and terminology servers, allowing the configuration of suitable application ontologies for distributed applications. The role is described that such servers, operatively coordinated in order to preserve semantic coherence, should play within a distributed Health-care Information System.

scholarly journals A Traveller Information System: Minimisation of the Number of Graphs’ Nodes Involved When Processing Route Requests

2014 ◽  
Vol 15 (4) ◽  
pp. 280-291 ◽  
Author(s):  
Zakaria Bendaoud ◽  
Karim Bouamrane
Keyword(s):  
Information System ◽  
Information Systems ◽  
Public Transport ◽  
Processing Route ◽  
Multi Agent System ◽  
Agent System ◽  
Multimodal Information ◽  
Calculation Process ◽  
Multi Agent ◽  
Voronoi Decomposition

Abstract The number of people using public transport is continuously increasing. Transport companies want to fulfil travellers’ expectations wherever possible. However, the great number of public transport companies operating in the same area can sometimes confuse travellers as to which route they should take and how to obtain the information relative to their journey. In this paper we suggest integrating several traveller information systems from different companies into the same multimodal information system, offering companies the choice not to share their data. This encourages them to join the system. Additionally, we have minimised the number of nodes involved when processing travellers’ requests in order to simplify the calculation process. To put our plan into action, we have opted for a multi-agent system coupled with the Voronoi decomposition for managing the network.

scholarly journals Implementasi Sistem Load Balancing Menggunakan Metode Least Time First Byte Dan Multi-Agent System Pada Lingkungan Virtual

2019 ◽  
Vol 4 (2) ◽  
pp. 63-70
Author(s):  
Dyah Ayu Wiranti ◽  
Kurnia Siwi Kinasih ◽  
Shinta Rizki Firdina Sugiono
Keyword(s):  
Information System ◽  
Load Balancing ◽  
Response Time ◽  
Service Provider ◽  
The Internet ◽  
Multi Agent System ◽  
Agent System ◽  
Time Value ◽  
Multi Agent ◽  
Modern Era

In this modern era, the technology is growing rapidly, the Internet is misled. This condition will be related to the service provider or commonly referred to as a server. Increasing the number of clients, the server also has to work heavier so that it often occurs overload. The Load Balancing mechanism uses the Least Time First Byte and Multi Agent system methods. This mechanism allows the server to overcome the number of users who perform service requests so that the load from the server can be resolved. This solution is considered efficient and effective because the request process on the information system will be shared evenly on multiple server back ends. The results of the research that can be proved if using this mechanism the server can work well when the request is from a user or client dating, this method successfully distributes the balancer evenly through the server backend. So the server is no longer experiencing overload. This can be proved when a system that has used the load balancing method with 300 connections generates a throughput of 123.1 KB/s as well as response time value of 4.72 MS and a system that does not use the load balancing method has a throughput of 108.4 KB/s as well as a response time value of 120.3 Ms. Therefore by implementing load balancing the performance of the system can always be improved.

scholarly journals STRATEGY SPACE EXPLORATION OF A MULTI-AGENT MODEL FOR THE LABOR MARKET

2006 ◽  
Vol 17 (03) ◽  
pp. 357-371 ◽  
Author(s):  
PABLO DE GRANDE ◽  
MANUEL EGUIA
Keyword(s):  
Labor Market ◽  
Space Exploration ◽  
Multi Agent System ◽  
Agent System ◽  
Market Mechanisms ◽  
Strategy Space ◽  
Trade Off ◽  
Agent Model ◽  
Simple Rules ◽  
Multi Agent

We present a multi-agent system where typical labor market mechanisms emerge. Based on a few simple rules, our model allows for different interpretative paradigms to be represented and for different scenarios to be tried out. We thoroughly explore the space of possible strategies both for those unemployed and for companies and analyze the trade-off between these strategies regarding global social and economical indicators.

Collaborative Multiagent Systems — an Alternative to Full Automation of Production

2020 ◽  
Vol 21 (7) ◽  
pp. 404-411
Author(s):  
V. V. Serebrenny
Keyword(s):  
Information System ◽  
Sensory Information ◽  
Physical Characteristics ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Collaborative System ◽  
Multi Agent ◽  
Full Automation

The paper proposes a new approach as an alternative to full automation of processes that meets current economic trends — collaborative multi-agent systems. In this concept, people and robots are considered as agents in a single sensory-information field, who perform tasks to achieve the goals of the collaborative multi-agent system. The urgency of collaborative multi-agent systems results from the fact that the industrial use of fully automated multi-component systems is limited by the financial and infrastructural unavailability of various industries to switch to completely unmanned technologies. The proposed approach combines the latest, but remaining quite recouped, technological advances along with highly skilled human labor. The use of collaborative multi-agent systems will be economically justified in the manufacture of products in small batches, in the conditions of rapid change of product lines, as well as the presence of staff shortages. The article shows that such an approach can significantly reduce automation costs, while ensuring that the specified production indicators are met. This approach allows taking a fresh look at a human, considering him and a robot as equal partners within a collaborative system. The basic concepts and distinctive characteristics of collaborative multi-agent systems are formulated and presented in the work, justifications for their use are given. Creating a new class of collaborative multi-agent systems requires solving a number of problems associated with the interaction of man and robot. The article considers issues related to the work of a person within a collaborative system, with a rational separation of human functions and an automated production system, in accordance with the necessary level of collaboration. The inclusion of a person with his psychoemotional and physical characteristics as an equivalent agent of a multi-agent system causes difficulties in formalizing collaborative multi-agent systems associated with the need to take these features into account and create a sensory-information system. The inclusion of a person with his psychoemotional and physical characteristics as an equivalent agent of a multi-agent system causes difficulties in formalizing collaborative multi-agent systems associated with the need to take these features into account and create a sensory-information system. The paper discusses ways to formalize a collaborative multi-agent system and management approaches.

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