The Use of Multi Agent Paradigm to Build an Agent Based Architecture for E-Commerce Application

In artificial intelligence research, agent-based systems technology has been hailed as a new paradigm for conceptualizing, designing, and implementing software systems. Agents are sophisticated computer programs that act autonomously on behalf of their users, across open and distributed environments, to solve a growing number of complex problems. Increasingly, however, applications require multiple agents that can work together. A multi-agent system (MAS) is a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver. There are many such real time applications which are very complex and beyond the scope of individual problem solver such as computer games simulation, population explosion problem, simulation of share market trading, aircraft maintenance, electronic book buying coalitions, military demining, wireless collaboration and communications, supply-chain management, joint mission planning and electronic commerce (online trading). The paper aims at developing a agent based architecture for supporting online trading using the multi agent systems platform. The present work has successfully implemented one such agent based environment for online fruit trading comprising of broadly three agents. This case study describes the implementation of a sample marketplace application called 'Fruit Market'. The objective is to enable the market participants to electronically trade tasty fruit over a network via their agents. Once we have a specification, the desired system can be situated within a domain that contains similar features and challenges. As the agents will exhibit trading behavior it is obvious that this application is best situated within the Multi-Agent Trading domain. This domain contains two role models: Distributed Marketplace and Institutional Auction, hence the next step is to consider which roles from the domain's role models best fit our specification. The details of selection of roles and responsibilities and implementation of agent architecture are discussed in the paper.