We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
— Tracking in crowded urban areas is a daunting task. High crowdedness causes challenging data association problems. Different motion patterns from a wide variety of moving objec...
As agent systems are solving more and more complex tasks in increasingly challenging domains, the systems themselves are becoming more complex too, often compromising their adapti...
This paper describes a patent awarded system for automatically marking the positions of stands for a trade fair or exhibition. The system has been in operation since August 2003 a...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...