Intelligent scientific computing systems

Until recently, most expert system building took place in the research departments of universities and a few major corporations. The primary emphasis was investigation of artificial intelligence principles, and the application was of secondary importance. The expert systems tools used reflect this interest. They are typically stand-alone AI computer systems, using special hardware and software environments (usually Lispr-based) not commonly fo md in scientific and engineering organizations. 

Most of the applications of artificial intelligence in chemistry so far have not involved numerical computation as a primary goal. Yet there are aspects of the AI approach to problem-solving which have relevance to computation. In scientific computation, one could view the knowledge base as the set of equations, input variable values, and unit conversions relevant to the problem, and the inference engine the numerical method used to solve the equations. This paper describes such a software system,... 

Advances in computer science continue to serve as the basis for new extensions to software products. In particular, artificial intelligence techniques have begun to mature to the point at which they can play a role in scientific software. In the future, scientific software will incorporate expert systems technology in order to provide a new level of assistance to scientists in applying statistical and graphical techniques to data analysis. 

This Springer journal focuses on research on the applications of computerbased methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks, and multi-agent systems. It aims to provide a forum for the presentation of scientific research and technological achievements accomplished by the international community. 

It is clear that analytical chemists would like a regression method that is able to cope with non-linearities whenever they are present (or when there are sound reasons to hypothesise their presence) in the dataset. Some methods have already been developed in other scientific areas (typically, computer science) to solve problems with conceptually similar difficulties namely, non-linear behaviours and a large amount of random noise. Artificial intelligence is a working field within computer science that tries to discover and describe how the human brain works and how can it be simulated by means of informatics systems (including software and hardware). This discipline has developed... 

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