We present two classes of distributed algorithms called DRBA and DOBA, for decentralized, proactive resource allocation in asynchronous real-time distributed systems. The objectiv...
— This paper is interested in reward maximization of periodic real-time tasks under a given energy constraint, where the reward received depends on how much computation a task ru...
This paper identifies five distinct mechanisms by which a population-based algorithm might have an advantage over a solo-search algorithm in classical optimization. These mechanism...
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Abstract. Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adap...