SENG 609.22 Agent base Software Engineering

An agent is a computer system capable of flexible autonomous action in a dynamic, unpredictable and open environment. Agent technologies and approaches have the potential to greatly impact the lives and work of all of us. Some application domains where agent technologies will play a crucial role include: Ambient Intelligence, the seamless delivery of ubiquitous computing, continuous communications and intelligent user interfaces to consumer and industrial devices; Grid Computing, where multi-agent system approaches will enable efficient use of the resources of high-performance computing infrastructure in science, engineering, medical and commercial applications; Electronic Business, where agent-based approaches are already supporting the automation and semi-automation of information gathering activities and purchase transactions over the Internet; the Semantic Web, where agents are needed both to provide services, and to make best use of the resources available, often in cooperation with others; Bio informatics and Computational Biology, where intelligent agents may support the coherent exploitation of the data revolution occurring in biology; and others including monitoring and control, resource management, and space, military and manufacturing applications, for example. Social simulation is the idea that one can build a computer program that models the behavior of some social phenomenon. Simulation can be applied in many critical areas and enables one to address issues before they these issues become problems. Simulation is more than just a technology, as it forces one think in global terms, about system behaviour, and about the fact that systems are more than the sum of their components. Simulation can provide insights into the designs of, for example, processes, architectures, or product lines before significant time and cost has been invested, and can be of great benefit in support of training. DEFINITION Simulation most general sense means to mimic, to do as if. More specifically it is used in research for any activity in which researchers make models, "simulation models", of the operation of some object of study. The merit of such an approach is that it enables researchers to play with the simulation model: they can enter hypothetical data to see what would happen, without having to let it happen in reality. Usually, simulation involves writing simulation models in a programming language or in a specialized simulation package, and running them on computers. [2]