Logic, Probability and Computation: Foundations and Issues of Statistical Relational AI
- 14:00 3rd February 2015 ( week 3, Hilary Term 2015 )Lecture Theatre B
Over the last 25 years there has been a considerable body of research into combinations of predicate logic and probability forming what has become known as statistical relational artificial intelligence (StaR-AI). Statistical relational artificial intelligence studies representing, reasoning and learning in uncertain and noisy domains described in terms of individuals and relations among individuals. We can model uncertainty about properties of individuals, relations among individuals, identity, and existence of individuals. I overview the foundations of the area, some research problems, proposed solutions, outstanding issues, and some misconceptions that have arisen. I discuss representations, semantics, inference, learning and applications, and provide references to the literature. This is intended to be an overview of foundations, rather than a survey of research results.