Abstract
After an introduction to Heuristic-Driven Theory Projection (HDTP) as framework for computational analogy-making, and a compact primer on parametrized complexity theory, we provide a complexity analysis of the key mechanisms underlying HDTP, together with a short discussion of and reflection on the obtained results. Amongst others, we show that restricted higher-order anti-unification as currently used in HDTP is W[1]-hard (and thus NP-hard) already for quite simple cases. Also, we obtain W[2]-hardness, and NP-completeness, for the original mechanism used for reducing second-order to first-order anti-unifications in the basic version of the HDTP system.
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Robere, R., Besold, T.R. (2012). Complex Analogies: Remarks on the Complexity of HDTP. In: Thielscher, M., Zhang, D. (eds) AI 2012: Advances in Artificial Intelligence. AI 2012. Lecture Notes in Computer Science(), vol 7691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35101-3_45
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DOI: https://doi.org/10.1007/978-3-642-35101-3_45
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