From Probabilistic Logics to Neurosymbolic AI

Abstract: 

A central challenge to contemporary AI is to integrate learning and reasoning. The integration of learning and reasoning has been studied for decades already in the fields of statistical relational artificial intelligence and probabilistic programming. Statistical relational AI has focussed on unifying logic and probability, the two key frameworks for reasoning, and has extended this probabilistic logics machine learning principles.

I will argue that StarAI and Probabilistic Logics form an ideal basis for developing neuro-symbolic artificial intelligence techniques. Thus neuro-symbolic computation = StarAI + Neural Networks.

Many parallels will be drawn between these two fields and will be illustrated using the Deep Probabilistic Logic Programming languages DeepProbLog and DeepStochLog.

Bio: 

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