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{tenorth10envmodel,
author = {Moritz Tenorth and Lars Kunze and Dominik Jain and Michael Beetz},
title = {{KNOWROB-MAP -- Knowledge-Linked Semantic Object Maps}},
booktitle = {10th IEEE-RAS International Conference on Humanoid Robots},
pages = {430-435},
month = {December 6-8},
year = {2010},
address = {Nashville, TN, USA},
bib2html_pubtype = {Conference Paper},
bib2html_rescat = {Perception, Models},
bib2html_groups = {K4C, EnvMod, ProbCog},
bib2html_funding = {CoTeSys},
bib2html_domain = {Assistive Household}
}