Learning to adapt and make real-time informed decisions in a dynamic complex environment is challenging problem. Monopoly popular strategic board game that requires players multiple during the game. Decision-making involves many real-world elements such as strategizing, luck, modeling of opponent’s policies. In this paper, we present novel representations for state action space full version def...

Abstract In this study, a novel auto-tuned hybrid deep learning approach composed of three base models, namely, long short-term memory, gated recurrent unit, and support vector regression, is developed to predict the fracture evolution process. The novelty framework lies in auto-determined hyperparameter configurations for each model based on Bayesian optimization technique, which guarantees fa...

Over the past few decades, volume of data has increased significantly in both scientific institutions and universities, with a large number students enrolled high related data. Furthermore, network traffic post-pandemic use online learning. Therefore, processing is complex challenging task that increases possibility intrusions anomalies. Traditional security systems cannot deal such high-speed ...