In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Abstract--We adapt methods originally developed in information and coding theory to solve some testing problems. The efficiency of two-stage pool testing of items is characterized ...
A no-reference image metric based on the singular value decomposition of local image gradients is proposed in this paper. This metric provides a quantitative measure of true image...
We propose a novel method for multi-robot plan adaptation which can be used for adapting existing spatial plans of robotic teams to new environments or imitating collaborative spat...
We propose a framework which we call stochastic offline programming (SOP). The idea is to embed the development of combinatorial algorithms in an off-line learning environment whi...