Combining artificial intelligence concepts with traditional simula tion methodologies yields a powerful design support tool known as knowledge based simulation. This approach turns a descrip tive simulation tool into a prescriptive tool, one which recom mends specific goals. Much work in the area of general goal pro cessing and explanation of recommendations remains to be done.

A knowledgeable person, in old times, has been regarded as a saint who knows everything without stepping out of house. Current technologies provide us with the ability of acquiring knowledge as one saint did before. Today, overloading of information always results in the quest for efficiently taking possession of useful information. With the advent of pervasive computing, information gathering is happening in real time. It has become possible that a collaborative knowledge network is constructed by utilizing little resource, but accurate under a carefully established environment. In this paper, we propose a new architecture, knowledge advantage machine (KaM), that helps people to construct a knowledge network. And we would like to apply a term, "call it once", into a novel type of knowledge discovery method. A typical User of KaM machine covers only one particular domain. The Domain information consists of a user defined ontology, a set of user collection of knowledge unit, we called them JANs, and some necessary tools to facilitate the knowledge discovery process. The "call it once" model transforms the traditional knowledge discovery process to a few basic simple steps (three steps).

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