pepl


Parameter estimation for SLPs with the Failure Adjusted Maximisation algorithm

Pepl implements and demonstrates parameter estimation (PE) in Stochastic Logic Programs (SLPs). It is an implementation the FAM algorithm [1]. For more information on how to use these programs see the user's guide and Prolog module documentation (see below). Pepl runs on the following Prolog systems:

licence

This software is distributed under the MIT licence.

installation and test

On Swi you can install with
?- pack_install( pepl ).

Test with

[library(pepl)].
[pack('pepl/examples/main')]
main.
main_store.
main_sample.
main_exact. (alias for main)

On Yap simply download the latest sources from pepl or github
cd to the Pepl's examples directory, start yap, and type

[main]. 
main.
main_store.
main_sample.
main_exact. (alias for main)

See main_* files in examples/ for more examples and doc/ for documentation.

highlights

This library has been developed and (only) tested on linux systems.
It is likely it will work on other oses with small modifications.

materials

user's guide: pepl-user_guide.pdf
module documentation: pepl.html
packed sources: pepl
sources on github pepl

references

[1] Nicos Angelopoulos, Notes on the Implementation of FAM.
In 3rd Workshop in Probabilistic Logic Programming (PLP'16)
September 3rd, 2016, London, UK

[2] James Cussens, Parameter estimation in stochastic logic programs.
Machine Learning, 44(3):245-271, 2001

author

Nicos Angelopoulos
---
London,
February 2017