While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
Abstract: Classification-based reinforcement learning (RL) methods have recently been proposed as an alternative to the traditional value-function based methods. These methods use...
Companies such as Zara and World Co. have recently implemented novel product development processes and supply chain architectures enabling them to make more product design and ass...
Abstract. In this paper, we present a separable, reusable middleware solution that provides coordinated, end-to-end QoS management over any type of service component, and can use e...
Denise J. Ecklund, Vera Goebel, Thomas Plagemann, ...
Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...