马尔可夫逻辑网络

所谓马尔可夫逻辑网（Markov logic network (MLN)），就是由一阶逻辑公式及其对应的权值组成的二元组集合。马尔可夫逻辑网络的基本思想是将一阶逻辑的限制放松，即一个事件违反公式越多，其发生概率越小，但未必为0。

參考文獻

外部連結 
 University of Washington Statistical Relational Learning group
 Alchemy 2.0: Markov logic networks in C++ 
 pracmln: Markov logic networks in Python 
 ProbCog: Markov logic networks in Python and Java that can use its own inference engine or Alchemy's
 markov thebeast: Markov logic networks in Java
 RockIt: Markov logic networks in Java (with web interface/REST API) 
 Tuffy: A Learning and Inference Engine with strong RDBMs-based optimization for scalability 
 Felix: A successor to Tuffy, with prebuilt submodules to speed up common subtasks 
 Factorie: Scala based probabilistic inference language, with prebuilt submodules for natural language processing etc 
 Figaro: Scala based MLN language 
 LoMRF: Logical Markov Random Fields, an open-source implementation of Markov Logic Networks in Scala 

贝叶斯统计
馬可夫網絡