Study of Framework and Categories of Agent Based Intelligent Systems

Abstract

In an Artificial Intelligence world, Agent-based technology is one of the most vibrant and important areas of RandD, emerging in the Information Technology in industry recent years. Intelligent Agent (IA) is an autonomous entity which observes, analyses and responds to an environment in order to achieve its expected goals. The Intelligent Agent has several categories such as Coordination, Integration, Mobility, Believable Agent and Assistance in achieving its expectancy. Agent Program is a tool / process which supports the IA Implementation. Agent program is defined briefly as a mathematical function of an IA which maps all the possible sequences of perceptions in every action. IA can respond either to a resulted coefficients or feedback elements or even to a function or constant which affects eventual actions. newlineThe main objective of this research work is to develop and implement different applications based on four IA categories which are Coordination, Integration, Believable Agent and Assistance. The first phase of research focuses on implementation of three categories i.e., coordination, integration and assistance. An agent-based prioritized email coordination is to organize unread emails of a particular user, based on the data that is populated from user s access history, for which the Coordination Category supports the implementation. E-learning is one of the major sources for students and public, providing knowledge. IA s integration category focuses on providing better access for e-learning resources in an effective way. This is achieved through populating and collating data for e-learning from heterogeneous data sources. In implementing IA s assistance category, Secured Trust model which plays critical role in open network is used. This work is carried out by analyzing and evaluating different factors in creating trust for the IA. newlineOur next phase of research focuses on implementation of IA s believable agent category and spam-filtering IA assistance category. In supporting our research, IA-based game application was developed and implemented for believable agent category. The Game Application uses the Game Theory - a mathematical study of rational behavior in strategic environment. There are a plethora of settings, most notably two-player zero-sum games in which the game theory provides strong and appealing solution concepts. These concepts were widely in use in creation of many game engines, such as Chess, Tic-Tac-Toe, etc. Various gaming techniques like MiniMax, Alpha-Beta Pruning, Hash Table and Evaluation were used in game engine creation. AI-based game engine evaluates the best moves using deep searching techniques and probabilistic reasoning used to optimize the computational capacity of an IA in an uncertain and imperfect informative environment. In the second proposed research, IA-based spam-filtering was developed. The concept of collaborative, personalized agent-based email spam-filtering, using Bayesian filtering as an agent-function, is proposed. It also discusses how the spam spreads through the mails. newline newline