Merging states in finite automata is a main method of reducing the size of the representation of regular languages. The process has been extensively studied for deterministic fi...
This paper's intention is to adapt prediction algorithms well known in the field of time series analysis to problems being faced in the field of mobile robotics and Human-Robo...
In this paper we present a technique for automatically generating constraints on parameter derivatives that reduce ambiguity in the behaviour prediction. Starting with a behaviour...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
This paper describes the evaluation of ERST, an adaptive system which is designed to improve its users' external representation (ER) selection accuracy on a range of database ...