Representation Formalisms

Here are some documents that will allow you to learn more about the representation formalisms supported by ProbCog. In particular, these documents explain theoretical aspects that are neglected in the practical tutorials.

Bayesian Logic Networks

• Dominik Jain, Stefan Waldherr and Michael Beetz: Bayesian Logic Networks, Technical Report, Technische Universität München, 2009
• Dominik Jain, Klaus von Gleissenthall and Michael Beetz: Bayesian Logic Networks and the Search for Samples with Backward Simulation and Abstract Constraint Learning, In 34th Annual German Conference on Artificial Intelligence (KI 2011), 2011

Markov Logic Networks

• Matthew Richardson and Pedro Domingos: Markov Logic Networks, Machine Learning, 62, 107-136, 2006
• Dominik Jain: Knowledge Engineering with Markov Logic Networks: A Review, In Proceedings of the Third Workshop on Dynamics of Knowledge and Belief (DKB 2011), 2011
• Dominik Jain, Andreas Barthels and Michael Beetz: Adaptive Markov Logic Networks: Learning Statistical Relational Models with Dynamic Parameters, 19th European Conference on Artificial Intelligence (ECAI), 2010