Guest Lecture

Enabling robots to perform complex manipulation tasks in open-world environments requires approaches to intelligence that bridge the traditional divide between symbolic and subsymbolic systems. Hybrid systems that combine reasoning over symbolic knowledge with probabilistically approximately correct inference over probability distributions promise to make robot manipulation actions generalizable, interpretable, and scalable to address real-world challenges. This