Efficient exploration with latent structure

Abstract

When interacting with a new environment, a robot can improve its online performance by efficiently exploring the effects of its actions. The efficiency of exploration can be expanded significantly by modeling and using latent structure to generalize experiences. We provide a theoretical development of the problem of exploration with latent structure, analyze several algorithms and prove matching lower bounds. We demonstrate our algorithmic ideas on a simple robot car repeatedly traversing a path with two different surface properties.