Design Of Intelligent Multi-agent System Research Articles

A Survey Paper on Particle Swarm Optimization based Routing Protocols in Mobile Ad-Hoc Networks

Swarm Intelligence is an artificial intelligence discipline which is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviours of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behaviour of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. The purpose of the research is to apply swarm intelligence on routing algorithms used in MANET. Swarm intelligence based routing algorithm will more promising for specific nature of adhoc networks and will outperform in real scenarios/constraints/environmental conditions and will tune and simulate to get an efficient and effective routing protocol for MANET.

A Computer Forensics Approach Based on Autonomous Intelligent Multi-Agent System

Due to the impact of wireless sensor networks (WSN) on dramatic reduction in computational and energy resources, research on the implications of this type of networks would be considered as a deliberate and update point. One of the main issues in these networks is the security. During transfer of data from source nodes to sink nodes or vice versa, many WSNs require applications to protect data privacy. Besides, computational and energy and memory limitations of WSNs and also defenseless environment that may be applied to them, make the possibility that these types of attacks occur more often. In this study, we provide a design using intelligent multi-agent systems that help us during the crime and after crime occurred to obtain more accurate forensics reports presentable to the court of law. A feature of the design of intelligent multi-agent system is to obtain evidence during crime, without the suspect realizing it; in fact, we can do live acquisitions. The proposed design was raised in WSN networks for first time. The investigation in firewall forensics consists of analyzing and interpreting information related to computer attacks which is contained in firewall log files. But the log files content is generally mysterious and difficult to decode. This paper proposes an intelligent system that automates the firewall forensics process and helps the security administrators to manage, exploit and interpret the firewall log file contents.

Comparative Analysis of Various Evolutionary Techniques of Load Balancing: A Review

a decade swarm Intelligence deals with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behavior of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. The aim of this review paper is to analyze and compare various swarm intelligence evolutionary techniques of load balancing and conclude the best optimum technique among them. A brief introduction of load balancing and its various evolutionary techniques are presented and summarized.

Book Reviews: When Humans and Agents Collide

Design of Intelligent Multi-Agent Systems: Human-Centredness, Architectures, Learning and Adaptation is a collection of papers whose content is grounded in two trends. First, soft-computing technologies have moved out of the laboratory and onto the Internet. Second, agent systems are being applied in areas such as engineering, process control, data mining, and e-business. In this context, three main problems arise: applying soft-computing agents in distributed environments, humanizing their interfaces, and optimizing the solutions they provide.