馬爾可夫邏輯網絡
所謂馬爾可夫邏輯網(Markov logic network (MLN)),就是由一階邏輯公式及其對應的權值組成的二元組集合。馬爾可夫邏輯網絡的基本思想是將一階邏輯的限制放鬆,即一個事件違反公式越多,其發生概率越小,但未必為0。
參考文獻
- 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. (原始內容存檔 (PDF)於2012-02-05).
外部連結
- University of Washington Statistical Relational Learning group
- Alchemy 2.0: Markov logic networks in C++ (頁面存檔備份,存於互聯網檔案館)
- pracmln: Markov logic networks in Python (頁面存檔備份,存於互聯網檔案館)
- ProbCog: Markov logic networks in Python and Java that can use its own inference engine or Alchemy's[失效連結]
- markov thebeast: Markov logic networks in Java
- RockIt: Markov logic networks in Java (with web interface/REST API) (頁面存檔備份,存於互聯網檔案館)
- Tuffy: A Learning and Inference Engine with strong RDBMs-based optimization for scalability (頁面存檔備份,存於互聯網檔案館)
- Felix: A successor to Tuffy, with prebuilt submodules to speed up common subtasks (頁面存檔備份,存於互聯網檔案館)
- Factorie: Scala based probabilistic inference language, with prebuilt submodules for natural language processing etc (頁面存檔備份,存於互聯網檔案館)
- Figaro: Scala based MLN language (頁面存檔備份,存於互聯網檔案館)
- LoMRF: Logical Markov Random Fields, an open-source implementation of Markov Logic Networks in Scala (頁面存檔備份,存於互聯網檔案館)