1.3k citations · 2.8k across the 15 of their papers we have counts for
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Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Thanh Thi Nguyen, Ngoc Duy Nguyen, Saeid Nahavandi
Reinforcement learning (RL) algorithms have been around for decades and employed to solve various sequential decision-making problems. These algorithms however have faced great cha…
Learning to Attend Relevant Regions in Videos from Eye Fixations
Thanh T. Nguyen, Dung Nguyen
Attentively important regions in video frames account for a majority part of the semantics in each frame. This information is helpful in many applications not only for entertainmen…
Multi-Agent Deep Reinforcement Learning with Human Strategies
Thanh Nguyen, Ngoc Duy Nguyen, Saeid Nahavandi
Deep learning has enabled traditional reinforcement learning methods to deal with high-dimensional problems. However, one of the disadvantages of deep reinforcement learning method…
A Human Mixed Strategy Approach to Deep Reinforcement Learning
Ngoc Duy Nguyen, Saeid Nahavandi, Thanh Nguyen
In 2015, Google's DeepMind announced an advancement in creating an autonomous agent based on deep reinforcement learning (DRL) that could beat a professional player in a series of…
A Review of Situation Awareness Assessment Approaches in Aviation Environments
Thanh Nguyen, Chee Peng Lim, Ngoc Duy Nguyen +2
Situation awareness (SA) is an important constituent in human information processing and essential in pilots' decision-making processes. Acquiring and maintaining appropriate level…
A Multi-Objective Deep Reinforcement Learning Framework
Thanh Thi Nguyen, Ngoc Duy Nguyen, Peter Vamplew +3
This paper introduces a new scalable multi-objective deep reinforcement learning (MODRL) framework based on deep Q-networks. We develop a high-performance MODRL framework that supp…