Kenneth M. Bayer

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While many real-world combinatorial problems can be advantageously modeled and solved using Constraint Programming, scalability remains a major issue in practice. Constraint models that accurately reflect the inherent structure of a problem, solvers that exploit the properties of this structure, and reformu-lation techniques that modify the problem encoding(More)
We present SOLVER, a Java applet that uses Constraint Processing (CP) techniques to assist human users in solving Sudoku puzzles. We also showcase CONSTRUCTOR, another applet that allows users to enter and store puzzles , which they can then load in SOLVER. These ap-plets are available from sudoku.unl.edu/Solver and su-doku.unl.edu/Constructor. Our goals(More)
Introduction We present a Java applet that uses Constraint Processing (CP) to assist a human in playing the popular game Minesweeper. Our goal is to illustrate the power of CP techniques to model and solve combinatorial problems in a context accessible to the general public. Minesweeper is a video game that has been included with Microsoft Windows since(More)
Constraint Programming is a powerful approach for modeling and solving many combinatorial problems, scalability, however, remains an issue in practice. Abstraction and reformulation techniques are often sought to overcome the complexity barrier. In this paper we introduce four reformulation techniques that operate on the various components of a Constraint(More)
The <i>building identification</i> (BID) problem is based on a process that uses publicly available information to automatically assign addresses to buildings in satellite imagery. In previous work, we have shown the advantages of casting the BID problem as a <i>Constraint Satisfaction Problem</i> (CSP) using the same generic constraint-model to represent(More)
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