Structure Of Multi-agent System Research Articles

A Secure E-commerce Environment Using Multi-agent System

Providing security for the customers in the e-commerce system is an essential issue. Providing security for each single online customer at the same time is considered a time consuming process. For a huge websites such task may cause several problems including response delay, losing the customer orders and system deadlock or crash, in which reduce system performance. This paper aims to provide a new prototype structure of multi agent system that solve the problem of providing security and avoid the problems that may reduce system performance. This is done by creating a software agent which is settled into the customer device to be responsible of purchase and encryption process without the customer interfering. The proposed agent avoids the problem of deadlock (i.e., break down) and the loss of requests which provides the required protection for information transmitted among all entities. Experimental results showed that employing software agent to manage purchase and encryption tasks improve system performance by 10% and increase system response time by 30.5%.

Empowering particle swarm optimization algorithm using multi agents’ capability: A holonic approach

A novel particle swarm optimization algorithm based on holonic structure in multi agent systems is presented. The proposed algorithm employs holonic structure of multi agent systems for optimizing numerical functions. Paying more attention, particle swarm optimization algorithm and multi agent systems are similar in first glance. Their similarities are based on the fact that both of them are population based and do their tasks cooperatively. In proposed approach, PSO is considered as a multi agent system and particles as agents. Multi agent systems use organizational design because of quantitative effect on their performance. One of these organizations is holonic structure. By using this structure, particles are arranged in different groups or holons and make a holarchy. In this holarchy, different groups or holons can communicate with each other in order to search space more efficiently, avoiding premature convergence and trapping in local optimums. Proposed structure helps PSO to maintain particles’ diversity and also makes a suitable balance between exploration and exploitation. The proposed algorithm is tested on a set of well-known test functions. Results have shown that the proposed algorithm is efficient, more accurate and outperforms other particle swarm optimization algorithms examined in this paper.

An ontology-driven multi-agent system for nautical chart generalization

ABSTRACTOn nautical charts, undersea features are portrayed by sets of soundings (depth points) and isobaths (depth contours) from which map readers can interpret undersea features. Different techniques were developed for automatic sounding selection and isobath generalization. These methods are mainly used to generate a new chart from the bathymetric database or from a larger scale chart through selection and simplification. However, a part of the process consists in selecting and emphasizing undersea features formed by groups of soundings and isobaths on the chart according to their relevance to maritime navigation. Hence, automation of the process requires classification of features and their generalization through the application of a set of operators according not only to geometric constraints but also to their meaning.The objective of this work is to conceive a multi-agent system (MAS) for nautical chart generalization that is driven by the knowledge on the generalization process and the undersea features and their relationships. First, this work provides a feature-centered ontology modeling of the generalization process. Then, the MAS structure is introduced where agents access cartographic knowledge stored in the ontology. The MAS makes use of measure algorithms to evaluate constraint violations on the chart in order to decide which generalization operators to apply. The whole model has been implemented to provide generalization plans on a real case study.

Cement industry control system based on multi agent

Cement production is characterized by its great capacity, long-time delay, multi variables, difficult measurement and multi disturbances. According to the distributed intelligent control strategy based on the multi agent, the multi agent control system of cement production is built, which includes integrated optimal control and diagnosis control. The distributed and multiple level structure of multi agent system for the cement control is studied. The optimal agent is in the distributed state, which aims at the partial process of the cement production, and forms the optimal layer. The diagnosis agent located on the diagnosis layer is the diagnosis unit which aims at the whole process of the cement production, and the central management unit of the system. The system cooperation is realized by the communication among optimal agents and diagnosis agent. The architecture of the optimal agent and the diagnosis agent are designed. The detailed functions of the optimal agent and the diagnosis agent are analyzed. At last the realization methods of the agents are given, and the application of the multi agent control system is presented. The multi agent system has been successfully applied to the off-line control of one cement plant with capacity of 5 000 t/d. The results show that the average yield of the clinker increases 9.3% and the coal consumption decreases 7.5 kg/t.

AN INTEGRATED MULTI-AGENT CSCW SYSTEM FOR CONCURRENT PRODUCT DEVELOPMENT

Product development capability is more and more important for an enterprise in a knowledge-based economic era. In the philosophy of concurrent engineering, product development should be carried out in a concurrent way. Computer support is necessary for Concurrent Product Development (CPD). As an excellent tool to meet complex needs, CSCW has been used in CPD. But nearly all CSCW systems that have been developed so far concentrate on a more or less narrow sub-field of cooperative work. Thus, the need of integrated CSCW applications are apparent. The agent is a suitable programming paradigm that can be used to meet the complex needs. In this paper, a P-PROCE (Process, Product, Resource, Organization, Control & Evaluation) model is introduced for CPD firstly. By categorizing the agents of the multi-agent system (MAS) into different types of agent according to P-PROCE model and offering a structure of MAS, the CPD is mapped to MAS. The cooperation among agents is very important for MAS. In the paper, a two-layer cooperation structure of MAS is proposed. In the macro layer, agent based workflow control the CPD process and in the micro layer the entity agents interact with each other directly to fulfill the task. The key issues of these two cooperation layers are discussed in the paper. Component based structure of agent and an implemented case are also provided in the paper.