This paper is based on understanding and matching interdisciplinary research activities in areas like health sciences, economic and those aiming to design a computer model for a software platform for the implementation of technological change. Transfer of information from the interdisciplinary research have an exceptionally important in successful market positioning of new technologies and strengthen the market position of those who implement these results. It also has the role of economic development in the context of global competition, leading to the progress of society.

The purpose of this paper is to present a combination of information technologies for access to information that characterizes the Web multidisciplinary systems using technological change. The platform presents a new concept in the Romanian scientific research and also a significant potential for growth and development, which may become an important factor in national and international scientific circles. The essence of this article is to propose an interaction between knowledge management and information stored in various forms (text-based documents or ideas unexposed) between individual researchers and/or various institutes with a goal of changing the mode of knowledge generation.

This paper presents some basic elements regarding the domain of the collaborative systems, a domain of maximum actuality and also the multi-agent systems, developed as a result of a sound study on the one-agent systems.

Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to “learn”. Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.

Expert systems use computational techniques that involve making decisions, just as human experts do, but it is well known that human experts may be wrong from time to time. We used to think that designing and using an expert system will solve this problem, but unfortunately expert systems can also be wrong, although the system contains no errors, but the knowledge on which the system is based, even if it is the best available, does not offer an answer, or the right answer for any situation. A wrong answer might cause a lot of harm if the system in question is one for medical use, or a management decision support. If the person using the system has no experience or solid knowledge about the area the system has been designed for, he or she will not be able to judge the accuracy of the given advice. Considering that real-world knowledge bases may contain a large number of rules, there will be a very large number of computational paths through an expert system, and each one of them will have to pass a test of correctness. More than ever, the risk management will be an important part of the entire process of the system’s project planning and management. For these reasons it is important for the software engineering expert to make sure the validation, verification and evaluation of the system are made at their best.