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...
Why is probabilistic roadmap (PRM) planning probabilistic? How does the probability measure used for sampling a robot’s configuration space affect the performance of a PRM plan...
— A long cherished goal in artificial intelligence has been the ability to endow a robot with the capacity to learn and generalize skills from watching a human teacher. Such an ...
This article investigates fundamental issues in scaling autonomous personal robots towards open-ended sets of everyday manipulation tasks which involve high complexity and vague j...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...