CSCI-8050: Knowledge Based Systems

The road map we plan to follow this semester is somewhat experimental in nature in that we will focus on three distinct areas of knowledge based systems: expert systems, intelligent database systems, and intelligent information systems.

Expert Systems are knowledge based systems that attempt to rival the performance of a human expert. Typically, a knowledge engineering task is undertaken to acquire expert domain knowledge from one or more human experts. This knowledge is coded using some useful representation scheme and possibly some expert system shell IDE. We will investigate the development of such a system (to the extent allowed within our time constraints).

Intelligent Database Systems integrate concepts from AI with those from the DB arena to form database systems with more capabilities than merely serving up facts to user queries. Active Databases may be considered a part of the Intelligent Database Systems domain since they use active triggers (i.e., rules) to initiate some internal database processing. Other types of rules may be incorporated into a database to derive values to "virtual" attributes during query processing. On another front, rules may be used to massage a user query in order to provide summary results instead of some large amount of tabular data.

Intelligent Information Systems bring together several types of systems to help with the decision making process. A typical IIS has several components including one or more databases, one or more expert systems, a structured interface, an intermediate working area (sometimes called a blackboard), one or more models that can be used for decision making or query response (i.e., using a forest regeneration simulation model to predict timber density at some point in the future), and its own processing routines. These components work together in a transparent fashion to aid user decision making. The infrastructure to support this seamless interaction among components is the real heart of an IIS.