Abstract
We present a Markov chain Monte Carlo algorithm that operates on generic model structures that are represented by terms found in the computed answers produced by stochastic logic programs. The objective of this paper is threefold (a) to show that SLD-trees are an elegant means for describing prior distributions over model structures (b) to sketch an implementation of the MCMC algorithm in Prolog, and (c) to provide insights on desirable properties for SLPs.
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Angelopoulos, N., Cussens, J. (2003). Prolog Issues and Experimental Results of an MCMC Algorithm. In: Bartenstein, O., Geske, U., Hannebauer, M., Yoshie, O. (eds) Web Knowledge Management and Decision Support. INAP 2001. Lecture Notes in Computer Science(), vol 2543. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36524-9_15
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DOI: https://doi.org/10.1007/3-540-36524-9_15
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