Abstract
The concept of Interchangeability was developed to deal with redundancy of values in the same domain. Conventional algorithms for detecting Neighborhood Interchangeability work by gradually establishing relationships between values from scratch. We propose the opposite strategy: start by assuming everything is interchangeable and disprove certain relations as more information arises. Our refutation-based algorithms have much better lower bounds whereas the lower bound and the upper bound of the traditional algorithms are asymptotically identical.
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Likitvivatanavong, C., Yap, R.H.C. (2008). A Refutation Approach to Neighborhood Interchangeability in CSPs. In: Wobcke, W., Zhang, M. (eds) AI 2008: Advances in Artificial Intelligence. AI 2008. Lecture Notes in Computer Science(), vol 5360. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89378-3_10
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DOI: https://doi.org/10.1007/978-3-540-89378-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89377-6
Online ISBN: 978-3-540-89378-3
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