The ProbCog project designs and implements a statistical relational learning and reasoning system that supports efficient learning and inference in relational domains.
One of the project's achievements was the development of an open-source toolbox for statistical relational learning and reasoning, which was specifically tailored towards the needs of technical systems.
This project was partly funded by CoTeSys.
@InProceedings{jain11blns,
author = {Dominik Jain and Klaus von Gleissenthall and Michael Beetz},
title = {{Bayesian Logic Networks and the Search for Samples with Backward Simulation and Abstract Constraint Learning}},
pages = {144-156},
booktitle = {KI 2011: Advances in Artificial Intelligence, 34th Annual German Conference on AI},
location = {Berlin, Germany},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {7006},
isbn = {978-3-642-24454-4},
month = {October 4-7},
year = {2011},
bib2html_groups = {ProbCog},
}