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.
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 14th International Conference on Applications of Prolog, (INAP 2001) |
| Subtitle of host publication | Lecture Notes in Artificical Intelligence |
| Publisher | Springer |
| Pages | 186-196 |
| Volume | 2543 |
| Publication status | Published - Sept 2002 |