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Sunday, June 30, 2019

Unifying Logical and Statistical AI With Markov Logic

As AI practitioners in the enterprise we understood this early on.   You need to know the results of statistical analysis AND the ability to link them usefully to logical decision making.   Sometimes easy,  sometimes not   Thus approaches like decision trees based on statistical data became popular for our team.   We understood too that Markov methods could provide the framework for providing this, so we experimented with them.  In both cases the results were also relatively transparent.    This unification can also outline way that humans will interact with the AI.  Research on the idea was going on then and is still now.  Below gives you a good update.  Starts basic and gets technical.

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:

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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