University of Oslo14d
IN-STK5100 – Reinforcement Learning and Decision Making Under Uncertainty
The aim of the course is two-fold. Firstly, to give a thorough understanding of statistical decision making, Markov decision processes, and the relation of statistical decision making to human ...
Cambridge University Press22d
Discounted cost exponential semi-Markov decision processes with unbounded transition rates: a service rate control problem with impatient customers
end{equation} The value iteration procedure is very useful in the applications of Markov decision processes. It can be used to compute the optimal value functions. It can also be used to prove ...
Frontiers24d
Decentralized multi-agent reinforcement learning based on best-response policies
Introduction: Multi-agent systems are an interdisciplinary research field that describes the concept of multiple decisive individuals interacting with a usually partially observable environment ...
Cambridge University Press8mon
Probability in the Engineering and Informational Sciences
This journal utilises an Online Peer Review Service (OPRS) for submissions. By clicking "Continue" you will be taken to our partner site https://mc.manuscriptcentral ...