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。
参考文献
- Richardson, Matthew; Domingos, Pedro. Markov Logic Networks (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).
外部链接
- University of Washington Statistical Relational Learning group
- Alchemy 2.0: Markov logic networks in C++ (页面存档备份,存于互联网档案馆)
- pracmln: Markov logic networks in Python (页面存档备份,存于互联网档案馆)
- ProbCog: Markov logic networks in Python and Java that can use its own inference engine or Alchemy's[失效链接]
- markov thebeast: Markov logic networks in Java
- RockIt: Markov logic networks in Java (with web interface/REST API) (页面存档备份,存于互联网档案馆)
- Tuffy: A Learning and Inference Engine with strong RDBMs-based optimization for scalability (页面存档备份,存于互联网档案馆)
- Felix: A successor to Tuffy, with prebuilt submodules to speed up common subtasks (页面存档备份,存于互联网档案馆)
- Factorie: Scala based probabilistic inference language, with prebuilt submodules for natural language processing etc (页面存档备份,存于互联网档案馆)
- Figaro: Scala based MLN language (页面存档备份,存于互联网档案馆)
- LoMRF: Logical Markov Random Fields, an open-source implementation of Markov Logic Networks in Scala (页面存档备份,存于互联网档案馆)