Rule compilation from constraint-based problem solving

Author

Subramanian, Suresh ; Freuder, Eugene C.

Author_Institution

Dept. of Comput. Sci., New Hampshire Univ., Durham, NH, USA

fYear

1990

fDate

6-9 Nov 1990

Firstpage

38

Lastpage

47

Abstract

A constraint-based system for automating the acquisition of problem-solving knowledge is described. The approach is novel in attempting to compile rules from the observation of constraint-based, relaxation-based problem solving. The system has three main components; a constraint-based problem solver, a rule-compiler and a rule-base problem solver. A relation consistency algorithm is the backbone of the constraint-based problem solver. One advantage of this method is that customized expert systems can be built by manipulating the problems used for learning. Experiments were performed to evaluate a prototype learning system and some extensions

Keywords

knowledge based systems; learning systems; logic programming; problem solving; constraint-based problem solver; constraint-based problem solving; constraint-based system; customized expert systems; problem-solving knowledge; prototype learning system; relation consistency algorithm; relaxation-based problem solving; rule-base problem solver; rule-compiler; Bones; Buildings; Computer science; Expert systems; Learning systems; Life testing; Problem-solving; Prototypes; Silver; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools for Artificial Intelligence, 1990.,Proceedings of the 2nd International IEEE Conference on

Conference_Location

Herndon, VA

Print_ISBN

0-8186-2084-6

Type

conf

DOI

10.1109/TAI.1990.130307

Filename

130307