TB1: SAT in AI: high performance search methods with applications
Tutorialists: Jussi Rintanen
Saturday, August 3rd, afternoon
SAT and its various extensions form a general and powerful framework for solving a number of important problems in AI. The tutorial introduces and explains the leading algorithms for SAT and its extensions and variants such as #SAT, MAX-SAT and QBF, as well as some of their most prominent applications in various subareas of AI, including machine learning and probabilistic reasoning, diagnosis, and planning.