Information Technology Reference
In-Depth Information
characteristic of KBMS is the integration of inference and query, which improves
the maintenance of the knowledge base, and provides useful development
environment for specific domain knowledge based systems.
Decision Support System (DSS) is evolved from the Management
Information System (MIS), with its concept initiated in the early 1970's. It
developed fast as an important tool to improve the competitiveness and
productivity of companies, as well as to decide on the successfulness of a
company. DSS has been adopted by various levels of decision makers in abroad,
and attracted great focuses in China. Decision support techniques are critical to
support scientific decision making. Early DSS is based on MIS and includes
some standard models, such as the operational research model and the
econometric model. In 1980, Ralph Sprague proposed a DSS structure based on
data base, model base and dialog generation and management software, which
has a great impact on later research and applications. In recent years, AI
technologies have been gradually applied to DSS, and thus came in to being the
intelligent decision support system (IDSS). In 1986, the author proposed the
intelligent decision system composed of data base, model base, and knowledge
base (Shi, 1988b), which improved the level of scientific management by
providing an effective means to solve semi-structured and ill-structured decision
problems. Characteristics of IDSS include the application of AI techniques to
DSS, and the integration of database and information retrieval techniques with
model based qualitative analysis techniques. In the 1990's, we developed the
Group DSS (GDSS) based on MAS technologies, which attracted enormous
research interests.
Building intelligent systems can imitate, extend and augment human
intelligence to achieve certain “machine intelligence”, which has great theoretical
meanings and practical values. Intelligent systems can be roughly classified into
four categories according to the knowledge contained and the paradigms
processed: single-domain single-paradigm intelligent system, multi-domain
single-paradigm intelligent system, single-domain multi-paradigm intelligent
system, and multi-domain multi-paradigm intelligent system.
1. Single-domain single-paradigm intelligent system
Such systems contain knowledge about a single domain, and process only
problems of a single paradigm. Examples of such systems include the first and
second generation of expert systems, as well as the intelligent control system.
