Treffer: To the gates of HAL: A HAL tutorial

Title:
To the gates of HAL: A HAL tutorial
Source:
FLOPS 2002 : functional and logic programming (Aizu, 15-17 September 2002)Lecture notes in computer science. :47-66
Publisher Information:
Berlin: Springer, 2002.
Publication Year:
2002
Physical Description:
print, 21 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Computer Science & Software Engineering, Monash University, Australia
Dept. of Computer Science, K.U.Leuven, Belgium
Dept. of Computer Science & Software Engineering, University of Melbourne, Australia
ISSN:
0302-9743
Rights:
Copyright 2003 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.14614869
Database:
PASCAL Archive

Weitere Informationen

Experience using constraint programming to solve real-life problems has shown that finding an efficient solution to the problem often requires experimentation with different constraint solvers or even building a problem-specific constraint solver. HAL is a new constraint logic programming language expressly designed to facilitate this process. It provides semi-optional type, mode and determinism declarations. These allow natural constraint specification by means of type overloading, better compile-time error checking and generation of more efficient run-time code. Importantly, it provides type classes which can be used to specify solver interfaces, allowing the constraint programmer to support modelling of a constraint problem independent of a particular solver, leading to easy plug and play experimentation with different solvers. Other interesting features include mutable global variables for implementing a constraint store, and dynamic scheduling and Constraint Handling Rules (CHRs) for combining, extending and writing new constraint solvers.