...Özge H. Namlı; Faranak Nouri; N. Serap Sengor; Seda Yanık; Osman Ogunclu; Yusuf M. Koyuncu Purpose This study proposes a novel hybrid artificial neural network (H-ANN) framework, inspired by reinforcement learning (RL), to proactively detect Internet connection speed problems using enriched...

...Miao Ye; Lin Qiang Huang; Xiao Li Wang; Yong Wang; Qiu Xiang Jiang; Hong Bing Qiu Purpose A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed. Design/methodology/approach First...

...Qiaoling Zhou Purpose English original movies played an important role in English learning and communication. In order to find the required movies for us from a large number of English original movies and reviews, this paper proposed an improved deep reinforcement learning algorithm...

...Yang Gao; Jan Peters; Antonios Tsourdos; Shao Zhifei; Er Meng Joo Purpose This purpose of this paper is to provide an overview of the theoretical background and applications of inverse reinforcement learning (IRL). Design/methodology/approach Reinforcement learning (RL) techniques provide...

... information to make decisions. Findings This work establishes an important theoretical link between classical population genetics, evolutionary computation theory and model free reinforcement learning methodology. Not only may the theory explain the success of the currently existing Monte‐Carlo tree...