Abstract
Given a set of variables, each of which has a domain of possible values, and a set of constraints that limit the acceptable set of assignments of values to variables, the goal of a CSP (Constraint Satisfaction Problem) is to find an assignment of values to the variables that satisfies all of the constraints. Picat provides three solver modules, including cp (Constraint Programming), sat (Satisfiability), and mip (Mixed Integer Programming), for modeling and solving CSPs. This chapter provides an introduction to modeling with constraints, with a primary focus on the cp module, and a secondary focus on the sat and mip modules.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
- 2.
Taken with permission from www.svor.ch/competitions/competition2007/AsroContestSolution.pdf.
- 3.
This is a relatively small problem instance of Kakuro. For larger and more difficult instances, see the website Kakuro Conquest (http://www.kakuroconquest.com/).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2015 The Author(s)
About this chapter
Cite this chapter
Zhou, NF., Kjellerstrand, H., Fruhman, J. (2015). Basic Constraint Modeling. In: Constraint Solving and Planning with Picat. SpringerBriefs in Intelligent Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-25883-6_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-25883-6_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25881-2
Online ISBN: 978-3-319-25883-6
eBook Packages: Computer ScienceComputer Science (R0)