Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Abstract This paper presents a methodology based on a variation of the Rapidlyexploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial veh...
Formal analysis can be used to verify that a model of the system adheres to its requirements. As such, traditional formal analysis focuses on whether known (desired) system propert...
This paper describes a novel approach to embedded software development. Instead of using a combination of C code and modeling tools, we propose an approach where modeling and progr...
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...