Constraints and AI planning

Author

Nareyek, Alexander ; Freuder, Eugene C. ; Fourer, Robert ; Giunchiglia, Enrico ; Goldman, Robert P. ; Kautz, Henry ; Rintanen, Jussi ; Tate, Austin

Author_Institution

Univ. Coll. Cork, Ireland

Volume

20

Issue

2

fYear

2005

Firstpage

62

Lastpage

72

Abstract

Tackling real-world planning problems often requires considering various types of constraints, which can range from simple numerical comparators to complex resources. This article provides an overview of techniques to deal with such constraints by expressing planning within general constraint-solving frameworks. Our goal here is to explore the interplay of constraints and planning, highlighting the differences between propositional satisfiability (SAT), integer programming (IP), and constraint programming (CP), and discuss their potential in expressing and solving AI planning problems.

Keywords

computability; constraint handling; graph theory; integer programming; planning (artificial intelligence); problem solving; artificial intelligence planning; constraint programming; constraint-solving; integer programming; problem solving; satisfiability; Artificial intelligence; Educational institutions; Integer linear programming; Linear programming; Problem-solving; Strips; Technology planning; Terminology; Uncertainty; constraint programming; integer programming; planning; propositional satisfiability;

fLanguage

English

Journal_Title

Intelligent Systems, IEEE

Publisher

ieee

ISSN

1541-1672

Type

jour

DOI

10.1109/MIS.2005.25

Filename

1413173