Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Abstract. While traditional approaches to machine learning are sensitive to highdimensional state and action spaces, this paper demonstrates how an indirectly encoded neurocontroll...
This paper provides some new techniques to construct a LyapunovKrasovskii functional for time varying delay systems. The construction is based on a partitioning scheme of the time...
In this paper we present a novel method for foreground segmentation. Our proposed approach follows a nonparametric background modeling paradigm, thus the background is modeled by ...
Martin Hofmann 0011, Philipp Tiefenbacher, Gerhard...
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...