Abstract
The problem of Causal Structure Discovery is defined by given inputs, outputs, auxiliary knowledge of components and possible internal connections. Constraints Programming is employed to discover admissible system models. Existence of internal connections and predefined functionality of components is handled through reification.
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Notes
- 1.
The library clpfd for constraint programming with finite domains was incorporated; see http://www.pathwayslms.com/swipltuts/clpfd/clpfd.html for details.
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Ligęza, A. (2017). An Experiment in Causal Structure Discovery. A Constraint Programming Approach. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_26
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DOI: https://doi.org/10.1007/978-3-319-60438-1_26
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