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
- Richardson, Matthew; Domingos, Pedro. (PDF). Machine Learning. 2006, 62 (1-2): 107–136 [2016-06-06]. doi:10.1007/s10994-006-5833-1. （原始内容存档 (PDF)于2012-02-05）.
外部連結
- University of Washington Statistical Relational Learning group
- Alchemy 2.0: Markov logic networks in C++ （页面存档备份，存于）
- pracmln: Markov logic networks in Python （页面存档备份，存于）
- 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) （页面存档备份，存于）
- Tuffy: A Learning and Inference Engine with strong RDBMs-based optimization for scalability （页面存档备份，存于）
- Felix: A successor to Tuffy, with prebuilt submodules to speed up common subtasks （页面存档备份，存于）
- Factorie: Scala based probabilistic inference language, with prebuilt submodules for natural language processing etc （页面存档备份，存于）
- Figaro: Scala based MLN language （页面存档备份，存于）
- LoMRF: Logical Markov Random Fields, an open-source implementation of Markov Logic Networks in Scala （页面存档备份，存于）
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