Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
—A material handling (MH) system of a general assembly line dispatching parts from inventory to working buffers could be complicated and costly to operate. Generally it is extrem...
— Target tracking has two variants that are often studied independently with different approaches: target searching requires a robot to find a target initially not visible, and ...
—We consider the situation where N nodes share a common access point. With each node i there is an associated buffer and channel state that change in time. Node i dynamically cho...
Eitan Altaian, Konstantin Avrachenkov, Nicolas Bon...