… the predicted future orders to optimize each sub-problem further. … a novel hierarchical
optimization framework to better solve … with different scales to optimize vehicles routes towards …

… In this paper, we propose a novel hierarchical framework for … The proposed hierarchical
framework comprises a global tier for … our proposed framework by investigating the optimal trade-…

… (HRL) decomposes a long-horizon reinforcement learning task into a hierarchy of … optimal
subtasks as the higher-level actions. A subtask may itself be a reinforcement learning problem …

… In this paper, we propose a hierarchical reinforcement learning (HRL) approach for relay
selection and power allocation, to minimize the outage probability of the two-hop cooperative …

… hierarchical optimization framework is proposed to optimize … a new hierarchical reinforcement
learning method to … of a two-level hierarchical framework in our method and each level …

… leads to unstable training. Instead, we propose a hierarchical RL framework to more efficiently
… [6, 7], we adopt a probabilistic graphical model framework for control, as demonstrated in …

… with trading cost via deep reinforcement learning. We propose a hierarchical reinforced
stock trading system (HRPM). Concretely, we build a hierarchy of portfolio management over …

… This paper develops a hierarchical reinforcement learning architecture for multimission …
develop a new optimization framework based on hierarchical reinforcement learning (HRL). …

… This study aims to apply Hierarchical Reinforcement Learning (HRL) and Options Framework
to control a signalized vehicular intersection and compare its performance with that of a …

… to hierarchical control architectures and associated learning … and hierarchical organization
that machine learning … of optimal policy stands in contrast to a hierarchically optimal …