Motion planning in dynamic environments consists of the generation of a collision-free trajectory from an initial to a goal state. When the environment contains uncertainty, preven...
Planning graphs have been shown to be a rich source of heuristic information for many kinds of planners. In many cases, planners must compute a planning graph for each element of ...
Daniel Bryce, William Cushing, Subbarao Kambhampat...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
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...