𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A multi-functional knowledge based system to learn, apply and consult procedures

✍ Scribed by Pablo R de Buen; Sunil Vadera; Eduardo F Morales


Book ID
104361345
Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
385 KB
Volume
15
Category
Article
ISSN
0957-4174

No coin nor oath required. For personal study only.

✦ Synopsis


One of the main challenges facing systems developers is to design systems with the flexibility and adaptability required to satisfy a professional user's needs. This paper presents a novel architecture and a knowledge representation scheme for a multi-functional adaptive system that support professional engineers that work with established procedures. The system achieves its multi-functionality by using a single knowledge representation scheme based on a set of modular networks. The developed representation is exploited by three operators that enable a user to learn, consult different procedures and solve problems. The representation also facilitates the automatic generation of problems and the identification of user errors. The integration of functionalities through a single representation produces a synergy that results in extra-functionality, flexibility and reduces the amount of development effort required. The system adapts to a user by using simple but efficient user modelling techniques that tailor the tutoring information. A rule-based mechanism is used to propose an agenda and a novel rule simplification algorithm is developed to help an expert to develop the rules for proposing the agenda. A prototype was developed and three civil engineering procedures were implemented to evaluate the architecture through scenarios and an empirical evaluation with real engineers.


πŸ“œ SIMILAR VOLUMES


A predicting system based on combining a
✍ Chen Jian πŸ“‚ Article πŸ“… 1993 πŸ› John Wiley and Sons 🌐 English βš– 494 KB

## Abstract In this paper a system is proposed and applied to predicting silicon content in pig iron for a blast furnace. It combines an adaptive predictor with a knowledge base. On‐line experiments show that the prediction accuracy of the system is much better than that of an experienced operator