Unifying Logical and Statistical AI with Markov Logic
By Pedro Domingos, Daniel Lowd
Communications of the ACM, July 2019, Vol. 62 No. 7, Pages 74-83 10.1145/3241978
For many years, the two dominant paradigms in artificial intelligence (AI) have been logical AI and statistical AI. Logical AI uses first-order logic and related representations to capture complex relationships and knowledge about the world. However, logic-based approaches are often too brittle to handle the uncertainty and noise present in many applications. Statistical AI uses probabilistic representations such as probabilistic graphical models to capture uncertainty. However, graphical models only represent distributions over propositional universes and must be customized to handle relational domains. As a result, expressing complex concepts and relationships in graphical models is often difficult and labor-intensive. .... " ( Full Technical paper)
Video intro to the concept (technical):
Alchemy Language, mentioned in the above talk:
https://alchemy.cs.washington.edu/
Alchemy: Open Source AI
Welcome to the Alchemy system! Alchemy is a software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation. Alchemy allows you to easily develop a wide range of AI applications, including: .... "
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